diff --git a/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip b/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip
index 0cd2dce..7c5202a 100644
Binary files a/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip and b/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip differ
diff --git a/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
index f807320..1dc32c0 100644
Binary files a/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip and b/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip differ
diff --git a/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip b/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip
index 0d90501..f32bfb9 100644
Binary files a/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip and b/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip differ
diff --git a/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip b/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip
index 899922f..a8bb609 100644
Binary files a/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip and b/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip differ
diff --git a/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip b/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip
index 0eeacc9..24c223a 100644
Binary files a/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip and b/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip differ
diff --git a/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
index e395a2a..ff88bd4 100644
Binary files a/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip and b/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip differ
diff --git a/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip b/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip
index bf4c32e..2004579 100644
Binary files a/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip and b/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip differ
diff --git a/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip b/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip
index 7c78b8a..ace662a 100644
Binary files a/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip and b/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip differ
diff --git a/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt b/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt
index 18bc26a..04fc9a7 100644
--- a/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt
+++ b/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt
@@ -554,7 +554,7 @@ randomization.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (1 minutes 9.382 seconds)
+   **Total running time of the script:** (1 minutes 7.044 seconds)
 
 **Estimated memory usage:**  705 MB
 
diff --git a/docs/_sources/auto_examples/plot_dcrt_example.rst.txt b/docs/_sources/auto_examples/plot_dcrt_example.rst.txt
index 5630a1f..1ebf5cd 100644
--- a/docs/_sources/auto_examples/plot_dcrt_example.rst.txt
+++ b/docs/_sources/auto_examples/plot_dcrt_example.rst.txt
@@ -162,7 +162,7 @@ Plotting the comparison
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (1 minutes 1.772 seconds)
+   **Total running time of the script:** (1 minutes 1.764 seconds)
 
 **Estimated memory usage:**  643 MB
 
diff --git a/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt b/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt
index 6a5f832..f662617 100644
--- a/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt
+++ b/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt
@@ -491,7 +491,7 @@ Analyze the results
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 8.364 seconds)
+   **Total running time of the script:** (0 minutes 8.271 seconds)
 
 **Estimated memory usage:**  626 MB
 
diff --git a/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt b/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt
index acd35f5..24bea20 100644
--- a/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt
+++ b/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt
@@ -180,11 +180,11 @@ You may choose a subject in [1, 2, 3, 4, 5, 6]. By default subject=2.
     Dataset created in /home/runner/nilearn_data/haxby2001
 
     Downloading data from https://www.nitrc.org/frs/download.php/7868/mask.nii.gz ...
-     ...done. (1 seconds, 0 min)
+     ...done. (0 seconds, 0 min)
     Downloading data from http://data.pymvpa.org/datasets/haxby2001/MD5SUMS ...
      ...done. (0 seconds, 0 min)
     Downloading data from http://data.pymvpa.org/datasets/haxby2001/subj2-2010.01.14.tar.gz ...
-
    Downloaded 15917056 of 291168628 bytes (5.5%,   17.6s remaining)
    Downloaded 52502528 of 291168628 bytes (18.0%,    9.2s remaining)
    Downloaded 91537408 of 291168628 bytes (31.4%,    6.6s remaining)
    Downloaded 130457600 of 291168628 bytes (44.8%,    5.0s remaining)
    Downloaded 169959424 of 291168628 bytes (58.4%,    3.6s remaining)
    Downloaded 209125376 of 291168628 bytes (71.8%,    2.4s remaining)
    Downloaded 248020992 of 291168628 bytes (85.2%,    1.2s remaining)
    Downloaded 287047680 of 291168628 bytes (98.6%,    0.1s remaining) ...done. (8 seconds, 0 min)
+
    Downloaded 110182400 of 291168628 bytes (37.8%,    1.6s remaining)
    Downloaded 249692160 of 291168628 bytes (85.8%,    0.3s remaining) ...done. (2 seconds, 0 min)
     Extracting data from /home/runner/nilearn_data/haxby2001/def37a305edfda829916fa14c9ea08f8/subj2-2010.01.14.tar.gz..... done.
     /opt/hostedtoolcache/Python/3.12.7/x64/lib/python3.12/site-packages/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected.
       warnings.warn(
@@ -284,7 +284,7 @@ Now, we compute p-values thanks to permutation tests applied to
  .. code-block:: none
 
     [Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    1.6s
-    [Parallel(n_jobs=1)]: Done 199 tasks      | elapsed:    6.3s
+    [Parallel(n_jobs=1)]: Done 199 tasks      | elapsed:    6.4s
 
 
 
@@ -365,7 +365,7 @@ However you might benefit from clustering randomization taking
  .. code-block:: none
 
     [Parallel(n_jobs=2)]: Using backend LokyBackend with 2 concurrent workers.
-    [Parallel(n_jobs=2)]: Done   5 out of   5 | elapsed:   32.3s finished
+    [Parallel(n_jobs=2)]: Done   5 out of   5 | elapsed:   33.4s finished
 
 
 
@@ -610,9 +610,9 @@ spurious discoveries.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (1 minutes 29.290 seconds)
+   **Total running time of the script:** (1 minutes 25.117 seconds)
 
-**Estimated memory usage:**  3331 MB
+**Estimated memory usage:**  3349 MB
 
 
 .. _sphx_glr_download_auto_examples_plot_fmri_data_example.py:
diff --git a/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt b/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt
index 73c0538..fbbdd31 100644
--- a/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt
+++ b/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt
@@ -205,9 +205,9 @@ Imports needed for this script
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (5 minutes 31.198 seconds)
+   **Total running time of the script:** (5 minutes 27.443 seconds)
 
-**Estimated memory usage:**  782 MB
+**Estimated memory usage:**  769 MB
 
 
 .. _sphx_glr_download_auto_examples_plot_knockoff_aggregation.py:
diff --git a/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt b/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt
index 0b3508b..8fa965d 100644
--- a/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt
+++ b/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt
@@ -176,7 +176,7 @@ Visualize the data
  .. code-block:: none
 
 
-    [<matplotlib.axis.YTick object at 0x7f2e590de7b0>, <matplotlib.axis.YTick object at 0x7f2e590bc710>, <matplotlib.axis.YTick object at 0x7f2e59034a70>, <matplotlib.axis.YTick object at 0x7f2d611c46e0>, <matplotlib.axis.YTick object at 0x7f2d611c7c50>, <matplotlib.axis.YTick object at 0x7f2d611c4950>, <matplotlib.axis.YTick object at 0x7f2d611c7110>, <matplotlib.axis.YTick object at 0x7f2d481c4d10>, <matplotlib.axis.YTick object at 0x7f2d611c5430>, <matplotlib.axis.YTick object at 0x7f2d611c60c0>]
+    [<matplotlib.axis.YTick object at 0x7fcb297db2c0>, <matplotlib.axis.YTick object at 0x7fcb297daf90>, <matplotlib.axis.YTick object at 0x7fcc17b51370>, <matplotlib.axis.YTick object at 0x7fcb299c8e90>, <matplotlib.axis.YTick object at 0x7fcb299c9ca0>, <matplotlib.axis.YTick object at 0x7fcb299c8170>, <matplotlib.axis.YTick object at 0x7fcb299c90a0>, <matplotlib.axis.YTick object at 0x7fcb297d8b00>, <matplotlib.axis.YTick object at 0x7fcb299c8cb0>, <matplotlib.axis.YTick object at 0x7fcb299cbef0>]
 
 
 
@@ -422,14 +422,14 @@ the features.
  .. code-block:: none
 
 
-    <matplotlib.legend.Legend object at 0x7f2d708236e0>
+    <matplotlib.legend.Legend object at 0x7fcb2945d6d0>
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 44.372 seconds)
+   **Total running time of the script:** (0 minutes 43.289 seconds)
 
 **Estimated memory usage:**  622 MB
 
diff --git a/docs/_sources/auto_examples/sg_execution_times.rst.txt b/docs/_sources/auto_examples/sg_execution_times.rst.txt
index bfe8edb..bd134f5 100644
--- a/docs/_sources/auto_examples/sg_execution_times.rst.txt
+++ b/docs/_sources/auto_examples/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**10:04.378** total execution time for 6 files **from auto_examples**:
+**09:52.927** total execution time for 6 files **from auto_examples**:
 
 .. container::
 
@@ -33,20 +33,20 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_plot_knockoff_aggregation.py` (``plot_knockoff_aggregation.py``)
-     - 05:31.198
-     - 782.5
+     - 05:27.443
+     - 769.2
    * - :ref:`sphx_glr_auto_examples_plot_fmri_data_example.py` (``plot_fmri_data_example.py``)
-     - 01:29.290
-     - 3331.0
+     - 01:25.117
+     - 3348.8
    * - :ref:`sphx_glr_auto_examples_plot_2D_simulation_example.py` (``plot_2D_simulation_example.py``)
-     - 01:09.382
+     - 01:07.044
      - 704.9
    * - :ref:`sphx_glr_auto_examples_plot_dcrt_example.py` (``plot_dcrt_example.py``)
-     - 01:01.772
-     - 642.6
+     - 01:01.764
+     - 643.1
    * - :ref:`sphx_glr_auto_examples_plot_variable_importance_classif.py` (``plot_variable_importance_classif.py``)
-     - 00:44.372
-     - 622.2
+     - 00:43.289
+     - 621.8
    * - :ref:`sphx_glr_auto_examples_plot_diabetes_variable_importance_example.py` (``plot_diabetes_variable_importance_example.py``)
-     - 00:08.364
-     - 626.5
+     - 00:08.271
+     - 626.2
diff --git a/docs/_sources/sg_execution_times.rst.txt b/docs/_sources/sg_execution_times.rst.txt
index 5117db5..48be8c4 100644
--- a/docs/_sources/sg_execution_times.rst.txt
+++ b/docs/_sources/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**10:04.378** total execution time for 6 files **from all galleries**:
+**09:52.927** total execution time for 6 files **from all galleries**:
 
 .. container::
 
@@ -33,20 +33,20 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_plot_knockoff_aggregation.py` (``../examples/plot_knockoff_aggregation.py``)
-     - 05:31.198
-     - 782.5
+     - 05:27.443
+     - 769.2
    * - :ref:`sphx_glr_auto_examples_plot_fmri_data_example.py` (``../examples/plot_fmri_data_example.py``)
-     - 01:29.290
-     - 3331.0
+     - 01:25.117
+     - 3348.8
    * - :ref:`sphx_glr_auto_examples_plot_2D_simulation_example.py` (``../examples/plot_2D_simulation_example.py``)
-     - 01:09.382
+     - 01:07.044
      - 704.9
    * - :ref:`sphx_glr_auto_examples_plot_dcrt_example.py` (``../examples/plot_dcrt_example.py``)
-     - 01:01.772
-     - 642.6
+     - 01:01.764
+     - 643.1
    * - :ref:`sphx_glr_auto_examples_plot_variable_importance_classif.py` (``../examples/plot_variable_importance_classif.py``)
-     - 00:44.372
-     - 622.2
+     - 00:43.289
+     - 621.8
    * - :ref:`sphx_glr_auto_examples_plot_diabetes_variable_importance_example.py` (``../examples/plot_diabetes_variable_importance_example.py``)
-     - 00:08.364
-     - 626.5
+     - 00:08.271
+     - 626.2
diff --git a/docs/auto_examples/plot_2D_simulation_example.html b/docs/auto_examples/plot_2D_simulation_example.html
index eb5a803..6e178db 100644
--- a/docs/auto_examples/plot_2D_simulation_example.html
+++ b/docs/auto_examples/plot_2D_simulation_example.html
@@ -475,7 +475,7 @@ <h2>Analysis of the results<a class="headerlink" href="#analysis-of-the-results"
 conservative. In practice, Type-1 Error guarantees seem to hold
 for a lower spatial tolerance. This is an additional benefit of clustering
 randomization.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 9.382 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 7.044 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  705 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-2d-simulation-example-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
diff --git a/docs/auto_examples/plot_dcrt_example.html b/docs/auto_examples/plot_dcrt_example.html
index e46446a..2079dcc 100644
--- a/docs/auto_examples/plot_dcrt_example.html
+++ b/docs/auto_examples/plot_dcrt_example.html
@@ -210,7 +210,7 @@ <h2>Plotting the comparison<a class="headerlink" href="#plotting-the-comparison"
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_dcrt_example_001.png" srcset="../_images/sphx_glr_plot_dcrt_example_001.png" alt="Type-I Error, Power" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 1.772 seconds)</p>
+<img src="../_images/sphx_glr_plot_dcrt_example_001.png" srcset="../_images/sphx_glr_plot_dcrt_example_001.png" alt="Type-I Error, Power" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 1.764 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  643 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-dcrt-example-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
diff --git a/docs/auto_examples/plot_diabetes_variable_importance_example.html b/docs/auto_examples/plot_diabetes_variable_importance_example.html
index 36e8bfd..81aa0fc 100644
--- a/docs/auto_examples/plot_diabetes_variable_importance_example.html
+++ b/docs/auto_examples/plot_diabetes_variable_importance_example.html
@@ -467,7 +467,7 @@ <h2>Analyze the results<a class="headerlink" href="#analyze-the-results" title="
   ax.set_xticklabels(diabetes.feature_names)
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 8.364 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 8.271 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  626 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-diabetes-variable-importance-example-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
diff --git a/docs/auto_examples/plot_fmri_data_example.html b/docs/auto_examples/plot_fmri_data_example.html
index 41e5ed6..700e5b9 100644
--- a/docs/auto_examples/plot_fmri_data_example.html
+++ b/docs/auto_examples/plot_fmri_data_example.html
@@ -247,19 +247,13 @@ <h2>Gathering and preprocessing Haxby dataset for a given subject<a class="heade
 Dataset created in /home/runner/nilearn_data/haxby2001
 
 Downloading data from https://www.nitrc.org/frs/download.php/7868/mask.nii.gz ...
- ...done. (1 seconds, 0 min)
+ ...done. (0 seconds, 0 min)
 Downloading data from http://data.pymvpa.org/datasets/haxby2001/MD5SUMS ...
  ...done. (0 seconds, 0 min)
 Downloading data from http://data.pymvpa.org/datasets/haxby2001/subj2-2010.01.14.tar.gz ...
 
-Downloaded 15917056 of 291168628 bytes (5.5%,   17.6s remaining)
-Downloaded 52502528 of 291168628 bytes (18.0%,    9.2s remaining)
-Downloaded 91537408 of 291168628 bytes (31.4%,    6.6s remaining)
-Downloaded 130457600 of 291168628 bytes (44.8%,    5.0s remaining)
-Downloaded 169959424 of 291168628 bytes (58.4%,    3.6s remaining)
-Downloaded 209125376 of 291168628 bytes (71.8%,    2.4s remaining)
-Downloaded 248020992 of 291168628 bytes (85.2%,    1.2s remaining)
-Downloaded 287047680 of 291168628 bytes (98.6%,    0.1s remaining) ...done. (8 seconds, 0 min)
+Downloaded 110182400 of 291168628 bytes (37.8%,    1.6s remaining)
+Downloaded 249692160 of 291168628 bytes (85.8%,    0.3s remaining) ...done. (2 seconds, 0 min)
 Extracting data from /home/runner/nilearn_data/haxby2001/def37a305edfda829916fa14c9ea08f8/subj2-2010.01.14.tar.gz..... done.
 /opt/hostedtoolcache/Python/3.12.7/x64/lib/python3.12/site-packages/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected.
   warnings.warn(
@@ -313,7 +307,7 @@ <h2>Making the inference with several algorithms<a class="headerlink" href="#mak
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    1.6s
-[Parallel(n_jobs=1)]: Done 199 tasks      | elapsed:    6.3s
+[Parallel(n_jobs=1)]: Done 199 tasks      | elapsed:    6.4s
 </pre></div>
 </div>
 <p>Now, let us run the algorithm introduced by Gaonkar et al. (c.f. References).
@@ -349,7 +343,7 @@ <h2>Making the inference with several algorithms<a class="headerlink" href="#mak
 </pre></div>
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[Parallel(n_jobs=2)]: Using backend LokyBackend with 2 concurrent workers.
-[Parallel(n_jobs=2)]: Done   5 out of   5 | elapsed:   32.3s finished
+[Parallel(n_jobs=2)]: Done   5 out of   5 | elapsed:   33.4s finished
 </pre></div>
 </div>
 </section>
@@ -472,8 +466,8 @@ <h2>Analysis of the results<a class="headerlink" href="#analysis-of-the-results"
 <div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">show</span><span class="p">()</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 29.290 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  3331 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 25.117 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  3349 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-fmri-data-example-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/931385a6992917f918857d6a3ee9f780/plot_fmri_data_example.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_fmri_data_example.ipynb</span></code></a></p>
diff --git a/docs/auto_examples/plot_knockoff_aggregation.html b/docs/auto_examples/plot_knockoff_aggregation.html
index 6d9fb42..39922ef 100644
--- a/docs/auto_examples/plot_knockoff_aggregation.html
+++ b/docs/auto_examples/plot_knockoff_aggregation.html
@@ -287,8 +287,8 @@ <h2>Imports needed for this script<a class="headerlink" href="#imports-needed-fo
 <li><img src="../_images/sphx_glr_plot_knockoff_aggregation_001.png" srcset="../_images/sphx_glr_plot_knockoff_aggregation_001.png" alt="FDR = 0.1, n = 500, p = 500, rho = 0.7" class = "sphx-glr-multi-img"/></li>
 <li><img src="../_images/sphx_glr_plot_knockoff_aggregation_002.png" srcset="../_images/sphx_glr_plot_knockoff_aggregation_002.png" alt="FDR = 0.1, n = 500, p = 500, rho = 0.7" class = "sphx-glr-multi-img"/></li>
 </ul>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (5 minutes 31.198 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  782 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (5 minutes 27.443 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  769 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-knockoff-aggregation-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/8635bd4b58b2828c710e4331f35d14f6/plot_knockoff_aggregation.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_knockoff_aggregation.ipynb</span></code></a></p>
diff --git a/docs/auto_examples/plot_variable_importance_classif.html b/docs/auto_examples/plot_variable_importance_classif.html
index fc8822a..d3f06cf 100644
--- a/docs/auto_examples/plot_variable_importance_classif.html
+++ b/docs/auto_examples/plot_variable_importance_classif.html
@@ -242,7 +242,7 @@ <h2>Visualize the data<a class="headerlink" href="#visualize-the-data" title="Li
 <a href="https://numpy.org/devdocs/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">axes</span></a><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">(</span><a href="https://numpy.org/devdocs/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">tck_ids</span></a><span class="p">,</span> <a href="https://numpy.org/devdocs/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a><span class="p">[</span><a href="https://numpy.org/devdocs/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">tck_ids</span></a><span class="p">])</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_variable_importance_classif_001.png" srcset="../_images/sphx_glr_plot_variable_importance_classif_001.png" alt="plot variable importance classif" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.axis.YTick object at 0x7f2e590de7b0&gt;, &lt;matplotlib.axis.YTick object at 0x7f2e590bc710&gt;, &lt;matplotlib.axis.YTick object at 0x7f2e59034a70&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d611c46e0&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d611c7c50&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d611c4950&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d611c7110&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d481c4d10&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d611c5430&gt;, &lt;matplotlib.axis.YTick object at 0x7f2d611c60c0&gt;]
+<img src="../_images/sphx_glr_plot_variable_importance_classif_001.png" srcset="../_images/sphx_glr_plot_variable_importance_classif_001.png" alt="plot variable importance classif" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.axis.YTick object at 0x7fcb297db2c0&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb297daf90&gt;, &lt;matplotlib.axis.YTick object at 0x7fcc17b51370&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb299c8e90&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb299c9ca0&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb299c8170&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb299c90a0&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb297d8b00&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb299c8cb0&gt;, &lt;matplotlib.axis.YTick object at 0x7fcb299cbef0&gt;]
 </pre></div>
 </div>
 </section>
@@ -439,10 +439,10 @@ <h2>Visualize the variable importance<a class="headerlink" href="#visualize-the-
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.legend.html#matplotlib.axes.Axes.legend" title="matplotlib.axes.Axes.legend" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">legend</span></a><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">handles</span></a><span class="o">=</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">handles</span></a> <span class="o">+</span> <span class="p">[</span><a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D" class="sphx-glr-backref-module-matplotlib-lines sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">important_legend</span></a><span class="p">,</span> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D" class="sphx-glr-backref-module-matplotlib-lines sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">ground_truth_legend</span></a><span class="p">],</span> <span class="n">loc</span><span class="o">=</span><span class="s2">&quot;upper right&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_variable_importance_classif_002.png" srcset="../_images/sphx_glr_plot_variable_importance_classif_002.png" alt="plot variable importance classif" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend object at 0x7f2d708236e0&gt;
+<img src="../_images/sphx_glr_plot_variable_importance_classif_002.png" srcset="../_images/sphx_glr_plot_variable_importance_classif_002.png" alt="plot variable importance classif" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend object at 0x7fcb2945d6d0&gt;
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 44.372 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 43.289 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  622 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-variable-importance-classif-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
diff --git a/docs/auto_examples/sg_execution_times.html b/docs/auto_examples/sg_execution_times.html
index 651bd0a..b9ea86c 100644
--- a/docs/auto_examples/sg_execution_times.html
+++ b/docs/auto_examples/sg_execution_times.html
@@ -110,7 +110,7 @@
       
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">¶</a></h1>
-<p><strong>10:04.378</strong> total execution time for 6 files <strong>from auto_examples</strong>:</p>
+<p><strong>09:52.927</strong> total execution time for 6 files <strong>from auto_examples</strong>:</p>
 <div class="docutils container">
 <style scoped>
 <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -132,28 +132,28 @@
 </thead>
 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_knockoff_aggregation.html#sphx-glr-auto-examples-plot-knockoff-aggregation-py"><span class="std std-ref">Knockoff aggregation on simulated data</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_knockoff_aggregation.py</span></code>)</p></td>
-<td><p>05:31.198</p></td>
-<td><p>782.5</p></td>
+<td><p>05:27.443</p></td>
+<td><p>769.2</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_fmri_data_example.html#sphx-glr-auto-examples-plot-fmri-data-example-py"><span class="std std-ref">Support recovery on fMRI data</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_fmri_data_example.py</span></code>)</p></td>
-<td><p>01:29.290</p></td>
-<td><p>3331.0</p></td>
+<td><p>01:25.117</p></td>
+<td><p>3348.8</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_2D_simulation_example.html#sphx-glr-auto-examples-plot-2d-simulation-example-py"><span class="std std-ref">Support recovery on simulated data (2D)</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_2D_simulation_example.py</span></code>)</p></td>
-<td><p>01:09.382</p></td>
+<td><p>01:07.044</p></td>
 <td><p>704.9</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_dcrt_example.html#sphx-glr-auto-examples-plot-dcrt-example-py"><span class="std std-ref">Distilled Conditional Randomization Test (dCRT) using Lasso vs Random Forest learners</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_dcrt_example.py</span></code>)</p></td>
-<td><p>01:01.772</p></td>
-<td><p>642.6</p></td>
+<td><p>01:01.764</p></td>
+<td><p>643.1</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_variable_importance_classif.html#sphx-glr-auto-examples-plot-variable-importance-classif-py"><span class="std std-ref">Measuring variable importance in classification</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_variable_importance_classif.py</span></code>)</p></td>
-<td><p>00:44.372</p></td>
-<td><p>622.2</p></td>
+<td><p>00:43.289</p></td>
+<td><p>621.8</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_diabetes_variable_importance_example.html#sphx-glr-auto-examples-plot-diabetes-variable-importance-example-py"><span class="std std-ref">Variable Importance on diabetes dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_diabetes_variable_importance_example.py</span></code>)</p></td>
-<td><p>00:08.364</p></td>
-<td><p>626.5</p></td>
+<td><p>00:08.271</p></td>
+<td><p>626.2</p></td>
 </tr>
 </tbody>
 </table>
diff --git a/docs/generated/hidimstat.PermutationImportance.html b/docs/generated/hidimstat.PermutationImportance.html
index ad30275..8d3d171 100644
--- a/docs/generated/hidimstat.PermutationImportance.html
+++ b/docs/generated/hidimstat.PermutationImportance.html
@@ -166,7 +166,7 @@ <h1>hidimstat.PermutationImportance<a class="headerlink" href="#hidimstat-permut
 <tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_params</span></code>([deep])</p></td>
 <td><p>Get parameters for this estimator.</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">predict</span></code>(X, y)</p></td>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">predict</span></code>(X[, y])</p></td>
 <td><p>Compute the prediction of the model with permuted data for each group.</p></td>
 </tr>
 <tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">score</span></code>(X, y)</p></td>
diff --git a/docs/searchindex.js b/docs/searchindex.js
index 2884c37..2fae57f 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"API": [[27, "api"]], "API Documentation": [[0, null]], "Analysis of the results": [[2, "analysis-of-the-results"], [5, "analysis-of-the-results"]], "Analyze the results": [[4, "analyze-the-results"]], "Build the documentation": [[27, "build-the-documentation"]], "Choosing inference parameters": [[2, "choosing-inference-parameters"]], "Classes": [[0, "classes"]], "Computation times": [[8, null], [28, null]], "Compute the p-values for the variable importance": [[7, "compute-the-p-values-for-the-variable-importance"]], "Computing z-score thresholds for support estimation": [[2, "computing-z-score-thresholds-for-support-estimation"]], "Define a function to compute the p-value from importance values": [[4, "define-a-function-to-compute-the-p-value-from-importance-values"]], "Dependencies": [[27, "dependencies"]], "Distilled Conditional Randomization Test (dCRT) using Lasso vs Random Forest learners": [[3, null]], "Documentation & Examples": [[27, "documentation-examples"]], "Estimators": [[0, "estimators"]], "Examples Gallery": [[1, null]], "Fit a baselien model on the diabetes dataset": [[4, "fit-a-baselien-model-on-the-diabetes-dataset"]], "Fit a baseline model on the diabetes dataset": [[4, "fit-a-baseline-model-on-the-diabetes-dataset"]], "Function to fetch and preprocess Haxby dataset": [[5, "function-to-fetch-and-preprocess-haxby-dataset"]], "Functions": [[0, "functions"]], "Gathering and preprocessing Haxby dataset for a given subject": [[5, "gathering-and-preprocessing-haxby-dataset-for-a-given-subject"]], "Generate the data": [[7, "generate-the-data"]], "Generating the data": [[2, "generating-the-data"]], "HiDimStat: High-dimensional statistical inference tool for Python": [[27, null]], "Imports needed": [[7, "imports-needed"]], "Imports needed for this script": [[2, "imports-needed-for-this-script"], [3, "imports-needed-for-this-script"], [4, "imports-needed-for-this-script"], [5, "imports-needed-for-this-script"], [6, "imports-needed-for-this-script"]], "Inference with several algorithms": [[2, "inference-with-several-algorithms"]], "Initializing FeatureAgglomeration object that performs the clustering": [[5, "initializing-featureagglomeration-object-that-performs-the-clustering"]], "Installation": [[27, "installation"]], "Knockoff aggregation on simulated data": [[6, null]], "Load the diabetes dataset": [[4, "load-the-diabetes-dataset"]], "Main references": [[27, "main-references"]], "Making the inference with several algorithms": [[5, "making-the-inference-with-several-algorithms"]], "Measure the importance of variables using the CPI method": [[4, "measure-the-importance-of-variables-using-the-cpi-method"]], "Measure the importance of variables using the LOCO method": [[4, "measure-the-importance-of-variables-using-the-loco-method"]], "Measure the importance of variables using the permutation method": [[4, "measure-the-importance-of-variables-using-the-permutation-method"]], "Measuring variable importance in classification": [[7, null]], "Other useful references": [[27, "other-useful-references"]], "Plotting the comparison": [[3, "plotting-the-comparison"]], "Plotting the results": [[5, "plotting-the-results"]], "Processing the computations": [[3, "processing-the-computations"]], "References": [[2, "references"], [4, "references"], [5, "references"], [6, "references"], [7, "references"], [27, "references"]], "Results": [[2, "results"]], "Specific plotting functions": [[2, "specific-plotting-functions"]], "Support recovery on fMRI data": [[5, null]], "Support recovery on simulated data (2D)": [[2, null]], "Variable Importance on diabetes dataset": [[4, null]], "Variable importance inference": [[7, "variable-importance-inference"]], "Visualize the data": [[7, "visualize-the-data"]], "Visualize the variable importance": [[7, "visualize-the-variable-importance"]], "hidimstat.CPI": [[9, null]], "hidimstat.LOCO": [[10, null]], "hidimstat.PermutationImportance": [[11, null]], "hidimstat.ada_svr": [[12, null]], "hidimstat.aggregate_quantiles": [[13, null]], "hidimstat.clustered_inference": [[14, null]], "hidimstat.data_simulation": [[15, null]], "hidimstat.desparsified_lasso": [[16, null]], "hidimstat.ensemble_clustered_inference": [[17, null]], "hidimstat.group_reid": [[18, null]], "hidimstat.hd_inference": [[19, null]], "hidimstat.knockoff_aggregation": [[20, null]], "hidimstat.model_x_knockoff": [[21, null]], "hidimstat.multivariate_1D_simulation": [[22, null]], "hidimstat.permutation_test_cv": [[23, null]], "hidimstat.reid": [[24, null]], "hidimstat.standardized_svr": [[25, null]], "hidimstat.zscore_from_pval": [[26, null]]}, "docnames": ["api", "auto_examples/index", "auto_examples/plot_2D_simulation_example", "auto_examples/plot_dcrt_example", "auto_examples/plot_diabetes_variable_importance_example", "auto_examples/plot_fmri_data_example", "auto_examples/plot_knockoff_aggregation", "auto_examples/plot_variable_importance_classif", "auto_examples/sg_execution_times", "generated/hidimstat.CPI", "generated/hidimstat.LOCO", "generated/hidimstat.PermutationImportance", "generated/hidimstat.ada_svr", "generated/hidimstat.aggregate_quantiles", "generated/hidimstat.clustered_inference", "generated/hidimstat.data_simulation", "generated/hidimstat.desparsified_lasso", "generated/hidimstat.ensemble_clustered_inference", "generated/hidimstat.group_reid", "generated/hidimstat.hd_inference", "generated/hidimstat.knockoff_aggregation", "generated/hidimstat.model_x_knockoff", "generated/hidimstat.multivariate_1D_simulation", "generated/hidimstat.permutation_test_cv", "generated/hidimstat.reid", "generated/hidimstat.standardized_svr", "generated/hidimstat.zscore_from_pval", "index", "sg_execution_times"], "envversion": {"sphinx": 64, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinxcontrib.bibtex": 9}, "filenames": ["api.rst", "auto_examples/index.rst", "auto_examples/plot_2D_simulation_example.rst", "auto_examples/plot_dcrt_example.rst", "auto_examples/plot_diabetes_variable_importance_example.rst", "auto_examples/plot_fmri_data_example.rst", "auto_examples/plot_knockoff_aggregation.rst", "auto_examples/plot_variable_importance_classif.rst", "auto_examples/sg_execution_times.rst", "generated/hidimstat.CPI.rst", "generated/hidimstat.LOCO.rst", "generated/hidimstat.PermutationImportance.rst", "generated/hidimstat.ada_svr.rst", "generated/hidimstat.aggregate_quantiles.rst", "generated/hidimstat.clustered_inference.rst", "generated/hidimstat.data_simulation.rst", "generated/hidimstat.desparsified_lasso.rst", "generated/hidimstat.ensemble_clustered_inference.rst", "generated/hidimstat.group_reid.rst", "generated/hidimstat.hd_inference.rst", "generated/hidimstat.knockoff_aggregation.rst", "generated/hidimstat.model_x_knockoff.rst", "generated/hidimstat.multivariate_1D_simulation.rst", "generated/hidimstat.permutation_test_cv.rst", "generated/hidimstat.reid.rst", "generated/hidimstat.standardized_svr.rst", "generated/hidimstat.zscore_from_pval.rst", "index.rst", "sg_execution_times.rst"], "indexentries": {"__init__() (hidimstat.cpi method)": [[9, "hidimstat.CPI.__init__", false]], "__init__() (hidimstat.loco method)": [[10, "hidimstat.LOCO.__init__", false]], "__init__() (hidimstat.permutationimportance method)": [[11, "hidimstat.PermutationImportance.__init__", false]], "ada_svr() (in module hidimstat)": [[12, "hidimstat.ada_svr", false]], "aggregate_quantiles() (in module hidimstat)": [[13, "hidimstat.aggregate_quantiles", false]], "clustered_inference() (in module hidimstat)": [[14, "hidimstat.clustered_inference", false]], "cpi (class in hidimstat)": [[9, "hidimstat.CPI", false]], "desparsified_lasso() (in module hidimstat)": [[16, "hidimstat.desparsified_lasso", false]], "ensemble_clustered_inference() (in module hidimstat)": [[17, "hidimstat.ensemble_clustered_inference", false]], "group_reid() (in module hidimstat)": [[18, "hidimstat.group_reid", false]], "hd_inference() (in module hidimstat)": [[19, "hidimstat.hd_inference", false]], "hidimstat.data_simulation": [[15, "module-hidimstat.data_simulation", false]], "knockoff_aggregation() (in module hidimstat)": [[20, "hidimstat.knockoff_aggregation", false]], "loco (class in hidimstat)": [[10, "hidimstat.LOCO", false]], "model_x_knockoff() (in module hidimstat)": [[21, "hidimstat.model_x_knockoff", false]], "module": [[15, "module-hidimstat.data_simulation", false]], "multivariate_1d_simulation() (in module hidimstat)": [[22, "hidimstat.multivariate_1D_simulation", false]], "permutation_test_cv() (in module hidimstat)": [[23, "hidimstat.permutation_test_cv", false]], "permutationimportance (class in hidimstat)": [[11, "hidimstat.PermutationImportance", false]], "reid() (in module hidimstat)": [[24, "hidimstat.reid", false]], "standardized_svr() (in module hidimstat)": [[25, "hidimstat.standardized_svr", false]], "zscore_from_pval() (in module hidimstat)": [[26, "hidimstat.zscore_from_pval", false]]}, "objects": {"hidimstat": [[9, 0, 1, "", "CPI"], [10, 0, 1, "", "LOCO"], [11, 0, 1, "", "PermutationImportance"], [12, 2, 1, "", "ada_svr"], [13, 2, 1, "", "aggregate_quantiles"], [14, 2, 1, "", "clustered_inference"], [15, 3, 0, "-", "data_simulation"], [16, 2, 1, "", "desparsified_lasso"], [17, 2, 1, "", "ensemble_clustered_inference"], [18, 2, 1, "", "group_reid"], [19, 2, 1, "", "hd_inference"], [20, 2, 1, "", "knockoff_aggregation"], [21, 2, 1, "", "model_x_knockoff"], [22, 2, 1, "", "multivariate_1D_simulation"], [23, 2, 1, "", "permutation_test_cv"], [24, 2, 1, "", "reid"], [25, 2, 1, "", "standardized_svr"], [26, 2, 1, "", "zscore_from_pval"]], "hidimstat.CPI": [[9, 1, 1, "", "__init__"]], "hidimstat.LOCO": [[10, 1, 1, "", "__init__"]], "hidimstat.PermutationImportance": [[11, 1, 1, "", "__init__"]]}, "objnames": {"0": ["py", "class", "Python class"], "1": ["py", "method", "Python method"], "2": ["py", "function", "Python function"], "3": ["py", "module", "Python module"]}, "objtypes": {"0": "py:class", "1": "py:method", "2": "py:function", "3": "py:module"}, "terms": {"": [2, 4, 7, 9, 10, 16, 24, 27], "0": [2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28], "00": [8, 23, 25, 28], "0001": [18, 24], "001": [12, 16], "01": [5, 6, 8, 16, 18, 23, 24, 25, 28], "01492149527525": 4, "02": [23, 25], "02351": 21, "02590": [2, 14, 17, 27], "03": [23, 25], "04": [8, 23, 25, 28], "05": [4, 6, 7, 8, 20, 23, 25, 28], "06": [23, 25], "07": [23, 25], "08": [8, 20, 28], "08885": 16, "09": [6, 8, 28], "0x7f2d481c4d10": 7, "0x7f2d611c46e0": 7, "0x7f2d611c4950": 7, "0x7f2d611c5430": 7, "0x7f2d611c60c0": 7, "0x7f2d611c7110": 7, "0x7f2d611c7c50": 7, "0x7f2d708236e0": 7, "0x7f2e59034a70": 7, "0x7f2e590bc710": 7, "0x7f2e590de7b0": 7, "1": [2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27], "10": [2, 3, 4, 5, 6, 7, 8, 9, 20, 22, 27, 28], "100": [2, 5, 22], "1000": [3, 23], "10000": [18, 24], "1010933404324": [4, 7], "1013699998": 20, "1023": [4, 7], "104": [13, 20], "1093": 6, "11": [2, 4], "1111": 6, "11195": 9, "11203": 9, "1166": [16, 27], "117921": [5, 27], "1186": 4, "119": [6, 20, 27], "1198": 20, "12": [2, 5, 7], "1202": [16, 27], "1214": [20, 27], "122": 6, "12265": 6, "13": [2, 6, 20], "130457600": 5, "13716": 16, "14": [2, 5], "1438606853": 27, "1471": 4, "15": [2, 3, 5, 16, 27], "151600911163946": 4, "154": 6, "15917056": 5, "16": 2, "1609": 9, "1610": 21, "1671": [13, 20], "1681": [13, 20], "169959424": 5, "17": [2, 5], "18": [2, 5, 6, 20], "19": 2, "1902": 16, "198": [6, 8, 28], "199": 5, "1d": [20, 21, 22], "1e": [4, 12, 16, 18, 24], "1e4": [18, 24], "2": [2, 3, 4, 5, 6, 7, 8, 9, 13, 16, 17, 18, 20, 24, 28], "20": [2, 5, 6, 7], "200": [2, 5], "2001": [4, 7, 20], "2007": 16, "2008": 4, "2009": [13, 20], "2010": 5, "2012": [5, 12], "2014": [2, 16, 27], "2015": 27, "2016": 24, "2017": 21, "2018": [6, 27], "2019": 16, "2020": [6, 16, 18, 20, 27], "2021": [2, 5, 14, 17, 27], "2023": [4, 6, 7, 9, 10, 27], "2024": [9, 27], "2055": 27, "2085": 27, "209125376": 5, "21": [2, 3], "2105": 4, "2106": [2, 14, 17, 27], "21600000000000003": 5, "217": [16, 27], "22": 2, "23": 2, "234": [5, 27], "24": 2, "240": 4, "242": [16, 27], "248020992": 5, "25": [5, 6, 7, 17, 20], "256": 4, "26": 6, "26090648721779": 4, "2722061930940729": 4, "2869": [16, 27], "287047680": 5, "287948367546456": 4, "28997": 9, "29": [5, 8, 20, 28], "290": [5, 8, 28], "2909": [16, 27], "291168628": 5, "2d": [1, 8, 21, 27, 28], "3": [2, 3, 4, 5, 6, 7, 12, 16, 17, 20, 27], "30": 7, "307": 4, "308": 5, "31": [5, 6, 8, 28], "3119253313517": 4, "32": [4, 5, 7], "33092885980301545": 4, "3331": [5, 8, 28], "33374807702299": 4, "34873505091371093": 4, "34h": 18, "34th": 27, "35": 24, "352999936251216": 4, "35323376775815": 4, "36": [4, 7, 9, 10], "3633702441001": 4, "364": [4, 8, 28], "36967014548640154": 4, "372": [7, 8, 28], "378": [8, 28], "37th": [6, 20, 27], "38": 9, "382": [2, 8, 28], "38th": 27, "4": [2, 3, 4, 5, 7, 16, 18, 24], "40": [2, 5, 7], "400": 7, "42": [16, 27], "43": 27, "44": [5, 7, 8, 28], "45": [4, 6, 7], "46114740610001137": 4, "46246416851449": 4, "47": 4, "479244269131684": 4, "48683083150894546": 4, "488": [13, 20], "49": [4, 5], "492": 5, "49274696": 6, "5": [2, 3, 4, 5, 6, 7, 8, 16, 20, 27, 28], "50": [4, 5, 7, 9, 11, 20], "500": [5, 6, 22], "5000": 16, "5048253747874585": 4, "51": 4, "52": 4, "5235794267120801": 4, "52502528": 5, "53": 4, "5316220308691071": 4, "5333394029342122": 4, "54": 4, "55": 4, "551": [6, 27], "5514585816057873": 4, "56": 4, "56629998": 6, "57429457038258": 4, "577": [6, 27], "58": [4, 5], "5858181205553151": 4, "59": 4, "5979566135054368": 4, "5e": 3, "6": [2, 3, 4, 5, 7, 8, 27, 28], "61": 4, "622": [7, 8, 28], "626": [4, 8, 28], "638": 27, "642": [8, 28], "643": 3, "646": 27, "65": 6, "665318862395647": 4, "666537166030764": 4, "67": 24, "67662": [4, 7, 9, 10], "67685": [4, 7, 9, 10], "683": 5, "69518424561582": 4, "7": [2, 3, 4, 5, 6, 7, 23, 25], "704": [8, 28], "705": 2, "71": 5, "723": [5, 12], "7236176985951": 4, "7283": [6, 20], "7293": [6, 20], "730": [5, 12], "74": 7, "7422256933791083": 5, "752": 7, "75372711094103": 4, "772": [3, 8, 28], "782": [6, 8, 28], "7868": 5, "8": [2, 3, 4, 5, 7], "80": [6, 7, 27], "85": 5, "86": 6, "9": [2, 3, 4, 5, 8, 23, 25, 28], "90": 7, "91537408": 5, "95": 16, "98": 5, "A": [2, 4, 5, 6, 7, 9, 10, 14, 16, 17, 18, 24, 27], "And": 7, "As": [2, 5, 27], "By": [5, 14, 16, 17, 19, 20], "For": [2, 5, 27], "If": [2, 9, 14, 16, 17, 18, 19, 20, 23, 27], "In": [2, 4, 5, 6, 7, 9, 10, 12, 18, 20, 27], "It": 5, "On": [16, 27], "One": [10, 14, 17, 19, 23, 26], "Or": 27, "The": [2, 3, 4, 5, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 23, 24, 25, 27], "Then": [2, 16], "To": [2, 4, 5, 7, 27], "_": [2, 3, 4, 5, 6], "_3": 6, "_551": 6, "_80": 6, "__": 3, "__init__": [9, 10, 11], "_coordinate_desc": 5, "_map_show": 5, "_slicer": 5, "aaai": [9, 27], "aarti": [6, 20], "ab": 7, "about": [2, 27], "abov": 20, "academ": 6, "accept": 26, "accord": 5, "account": 2, "accur": [2, 14, 17, 19, 23, 26], "achim": 4, "activ": [2, 5], "ad": 5, "ada": 5, "ada_svr": 5, "adapt": [5, 13, 17, 20], "adaptive_aggreg": 20, "adaptive_permutation_threshold": 5, "add": [2, 5], "add_one_subplot": 2, "addit": [2, 5, 16, 22], "adjust": [5, 16], "advanc": [4, 7, 9, 10, 27], "advantag": 2, "advoc": 5, "affect": 4, "aforement": 27, "after": [2, 4], "ag": 7, "against": [16, 18], "aggreg": [1, 2, 5, 8, 13, 17, 20, 27, 28], "aggregated_ev": 20, "aggregated_ko_select": 6, "aggregated_pv": 20, "agnost": [4, 7], "ahmad": [4, 7, 9, 10], "aim": [2, 4, 5], "ako": 27, "al": [2, 4, 5, 6, 7, 9, 10, 12, 20, 21], "alexi": [6, 20], "algorithm": [9, 10, 14, 17, 27], "all": [1, 5, 14, 16, 17, 20, 28], "allow": 5, "along": 20, "alpha": [3, 4, 6, 7, 16], "alpha_max": [16, 18, 24], "alpha_max_fract": 16, "alpha_min": [18, 24], "alreadi": 5, "also": [2, 4, 5, 7, 16, 18, 27], "alwai": 16, "american": [13, 20], "among": [2, 5], "an": [2, 4, 6], "anat": 5, "anatom": 5, "ani": [4, 5], "ann": [4, 20], "annal": [16, 27], "anoth": 5, "ao": [20, 27], "aos1337": 27, "append": [2, 3, 4, 6, 7], "appli": [2, 3, 5, 20], "applic": [16, 27], "appreci": 27, "approach": 4, "approxim": 5, "ar": [2, 3, 4, 5, 7, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 23, 24, 27], "arang": [4, 7], "argu": 2, "argument": [14, 17, 19], "arlot": [6, 20, 27], "around": 5, "arrai": [4, 7, 12, 16, 20, 21, 23, 24, 25], "articl": [6, 9, 27], "artifici": [9, 27], "arxiv": [2, 6, 14, 16, 17, 21, 27], "asarrai": 5, "assess": [4, 7, 9, 10, 27], "assist": [5, 12, 27], "associ": [4, 6, 7, 9, 10, 13, 20, 27], "assum": [5, 26], "astyp": 5, "asymptot": [16, 27], "augustin": 4, "austria": 27, "auto_exampl": 8, "auto_examples_jupyt": 1, "auto_examples_python": 1, "autoregress": 18, "avail": [2, 14, 16, 17, 19, 27], "averag": 2, "avoid": 16, "ax": [2, 3, 4, 7], "axhlin": [3, 4], "axi": [2, 4, 7], "axvlin": 7, "b": [2, 5, 6, 7, 12, 14, 16, 17, 18, 27], "back": 5, "backend": 5, "bar": 4, "barber": [6, 27], "base": [3, 4, 5, 7, 12, 21], "becaus": 7, "been": [16, 27], "befor": [4, 14, 17, 19, 20, 21], "beforehand": 16, "behavior": 5, "being": [13, 17], "bellec": 16, "below": [2, 5], "benefit": [2, 5, 7], "benjamini": 20, "berlin": [5, 12], "bertrand": [4, 6, 7, 9, 10, 20], "best": 6, "beta": [2, 22], "beta_1": 7, "beta_2": 7, "beta_3": 7, "beta_extend": 2, "beta_hat": [2, 5, 12, 14, 16, 17, 18, 19, 24, 25], "better": 5, "between": [2, 4, 5, 7, 18, 22], "bg_img": 5, "bh": 20, "bhq": 20, "bhy": 20, "bias": [4, 16, 27], "binari": 7, "binh": [6, 20], "bioinformat": 4, "bisect": 4, "bit": 2, "black": 7, "blue": [6, 7], "bmc": 4, "bmi": 7, "bodi": 7, "bonferroni": [2, 5], "bool": [5, 16, 18, 20, 21, 22], "bootstrap": 20, "both": [2, 4], "bottom": 2, "boulesteix": 4, "bound": [2, 6, 16], "box": 7, "box1": 7, "boxplot": [3, 6, 7], "brain": 5, "break": [2, 4, 22], "breiman": [4, 7], "briefli": 2, "buid": 4, "build": [2, 5, 14, 17], "bunch": 5, "bypass": 4, "byte": 5, "b\u00fchlmann": [13, 16, 20, 27], "c": [2, 5, 6, 7, 12, 16, 23, 25, 27], "cach": [14, 16, 17, 19, 20], "cal_fdp_pow": 6, "calcul": [20, 21], "call": [2, 5], "callabl": [9, 10, 11], "can": [2, 5, 6, 7, 9, 27], "canada": 27, "cand": 21, "cand\u00e8": [6, 27], "cap": 7, "captur": 7, "carolin": 4, "case": [2, 4], "caus": 7, "cb_max": [2, 16], "cb_min": [2, 16], "cc": [4, 7, 9, 10], "cd": 27, "cd_fast": 5, "cdot": 7, "celentano": 16, "center": [16, 20, 21], "cf": [13, 16], "cham": 27, "chamma": [4, 7, 9, 10, 27], "chang": 5, "check": [4, 5, 16, 18, 24], "check_random_st": 6, "chevali": [2, 5, 6, 14, 17, 18, 20, 27], "choic": [2, 5], "choos": 5, "chunk": 5, "citat": 27, "class": [9, 10, 11, 20], "classif": [1, 5, 8, 12, 20, 28], "clip": 4, "clone": [4, 7, 9, 27], "close": [2, 5, 14, 17, 19, 23, 26], "closer": 2, "cludl": [2, 5], "cluster": [2, 14, 17, 19, 20, 27], "clustered_infer": [2, 5], "cm": 4, "cmap": 7, "code": [1, 2, 3, 4, 5, 6, 7, 16, 18, 24], "coef0": 7, "coeffici": [3, 6], "color": [3, 4, 6, 7], "colormap": 4, "column": [4, 16], "com": [6, 27], "combin": [5, 7], "command": 27, "compar": [2, 3, 4, 5], "comparison": [5, 12], "compat": [9, 10, 11], "compress": [2, 5, 14, 17], "comput": [5, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 23, 26, 27], "compute_pv": 4, "concat": 4, "concept": 2, "concern": 2, "concurr": 5, "condit": [1, 4, 5, 7, 8, 9, 10, 27, 28], "condition_mask": 5, "confer": [4, 5, 6, 7, 9, 10, 12, 18, 20, 27], "confid": [5, 16, 27], "connect": [2, 5], "consecut": 18, "conserv": [2, 5], "consid": [2, 5, 7, 13, 16, 17, 18], "consider": [7, 16], "consist": [2, 5], "constant": 18, "constrain": 6, "construct": [2, 20, 21], "construct_method": 20, "contain": [2, 4, 5, 16, 23, 25], "context": [7, 27], "continu": [16, 18, 24], "contrarili": 7, "contrast": 5, "contribut": 27, "control": [2, 4, 5, 6, 7, 14, 17, 18, 20, 21, 24, 27], "converg": 5, "convergencewarn": 5, "coolwarm": 7, "corner": 2, "corr_mat": 7, "correct": [2, 5, 14, 17, 19, 23], "correction_clust": [2, 5], "correction_no_clust": 2, "correl": [2, 3, 4, 5, 6, 7, 18, 20, 21, 22], "correspond": [2, 5, 7, 20], "cortex": 5, "costli": 4, "cov_estim": [20, 21], "cov_hat": 18, "covari": [9, 10, 18, 20, 21], "covariate_estim": 4, "cpi": 7, "cpi_importance_list": 4, "cpi_linear": 7, "cpi_non_linear": 7, "cpi_pval": 4, "cpi_vim_arr": 4, "cpu": [14, 16, 17, 18, 19, 23, 24, 25], "creat": [2, 4, 5], "cross": [4, 7, 18, 23, 24, 25], "cumul": 23, "curran": [4, 7, 9, 10], "current": [2, 14, 16, 17, 19], "cut_coord": 5, "cutoff": 12, "cv": [5, 7], "d": [2, 7, 27], "d0crt": 3, "d60e14c19cd6e0fc38556ad29ac8fbc9": [4, 7, 9, 10], "daniel": 20, "data": [1, 4, 8, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28], "data_simul": 6, "datafram": [4, 5], "dataset": [1, 2, 8, 27, 28], "daum\u00e9": [6, 20], "davatziko": [5, 12], "dcrt": [1, 8, 28], "dcrt_zero": 3, "de": [2, 16, 27], "deal": 2, "decemb": 21, "decision_funct": [7, 9, 10, 11], "decod": [5, 27], "def": [2, 4, 5, 6], "def37a305edfda829916fa14c9ea08f8": 5, "default": [5, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 23, 24, 25, 26], "defin": [2, 20], "degre": [4, 7, 16], "delta": 2, "demonstr": 4, "deni": [4, 7, 9, 10], "depend": [2, 4, 5, 20], "deprec": 4, "derandom": 6, "derandomis": 6, "deriv": [2, 5, 12], "describ": [2, 6, 10], "design": [2, 16, 21, 22], "desir": [6, 20, 21], "desparsifi": [2, 5, 14, 16, 17, 18, 19, 27], "desparsified_lasso": 2, "destroi": 4, "detail": [2, 27], "determin": 23, "develop": 27, "deviat": [2, 7, 12, 18, 22, 24, 25], "dezeur": [16, 27], "df_plot": 4, "diabet": [1, 8, 28], "diamet": 2, "diamond": 7, "did": 5, "diff": 7, "differ": [2, 5, 7, 9, 27], "dim": 5, "dimens": 2, "dimension": [2, 4, 5, 6, 9, 13, 14, 16, 17, 19, 20, 21], "directli": [4, 18], "directori": [14, 16, 17, 19, 20], "discimin": 5, "discov": 5, "discoveri": [2, 5, 6, 7, 20, 21, 27], "discrimin": 5, "displai": 5, "distanc": 2, "distil": [1, 8, 28], "distrib": 26, "distribut": [5, 6, 7, 23, 26], "divid": [2, 5], "do": [2, 5, 20, 21], "doc": 27, "doe": [2, 4, 5], "dof_ajdust": 16, "doi": [4, 6, 7, 9, 20, 27], "done": [5, 14, 16, 17, 19, 20], "download": [1, 2, 3, 4, 5, 6, 7, 27], "dramat": 2, "draw": 2, "drawback": 6, "drop": 4, "dual": [16, 18, 24], "dualiti": 5, "due": [2, 5], "dure": [14, 16, 18, 19, 23, 24, 25], "e": [2, 4, 5, 6, 20, 23, 25, 27], "each": [9, 16, 18, 27], "eas": [2, 4], "ebh": 20, "ecdl": 27, "edg": 2, "editor": [4, 6, 7, 9, 10, 20], "eeg": [18, 27], "effect": [14, 17, 19, 23, 26], "either": 21, "elaps": 5, "els": [2, 5, 6], "emmanuel": [6, 21], "empir": [6, 20, 21], "empti": 5, "enabl": 2, "encludl": [2, 5], "end": [2, 3, 4, 5, 6, 7], "enet_coordinate_descent_gram": 5, "enfold": 2, "engemann": [4, 7, 9, 10, 27], "ensembl": [2, 5, 17, 27], "ensemble_clustered_infer": [2, 5], "ensembling_method": 17, "ensur": 16, "enumer": [4, 7], "ep": [18, 24], "epsilon": [2, 7], "equal": [2, 16, 23], "equi": [20, 21], "equival": [20, 21], "error": [2, 3, 24], "estim": [3, 4, 5, 6, 7, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 24, 25, 26], "et": [2, 4, 5, 6, 7, 9, 10, 12, 20, 21], "euclid": 27, "eval": 20, "eval_select": 6, "evalu": [9, 10, 11], "everi": [2, 14, 17, 18], "exampl": [2, 3, 4, 5, 6, 7, 8, 28], "exclus": 4, "execut": [8, 28], "executor": 7, "exemplifi": 7, "exhibit": [2, 6], "exp": 7, "expect": 5, "experi": 2, "express": 7, "extern": 7, "extract": 5, "f": [2, 3, 4, 5, 6, 7, 27], "face": 5, "fail": 7, "fake": 4, "fals": [2, 3, 5, 6, 7, 16, 20, 21, 27], "fan": [6, 21, 27], "fdp": 6, "fdp_eval": 6, "fdp_mx": 6, "fdp_pval": 6, "fdps_eval": 6, "fdps_mx": 6, "fdps_pval": 6, "fdr": [6, 20, 21], "fdr_control": 20, "feasibl": 2, "featur": [2, 5, 7, 22], "feature_extract": [2, 5], "feature_nam": 4, "featureagglomer": [2, 14, 17], "fetch_haxbi": 5, "fig": [2, 3, 4, 7], "figsiz": [2, 3, 6, 7], "figur": 6, "file": [4, 5, 7, 8, 9, 10, 28], "filter": 2, "final": [2, 5, 7], "finish": 5, "first": [2, 5, 7, 17], "fit": 7, "fit_i": 18, "fit_transform": 5, "fix": [4, 20], "fixedloc": 4, "flatten": 2, "flier": 7, "float": [12, 13, 14, 16, 17, 18, 20, 21, 22, 23, 24], "fmri": [1, 8, 27, 28], "fmri_filenam": 5, "fmri_mask": 5, "focu": 5, "fold": [4, 7], "follow": [2, 4, 27], "font": [3, 6], "forest": [1, 4, 7, 8, 28], "formal": 2, "formul": 5, "formula": [7, 13, 17], "four": 2, "foygel": 6, "fr": 5, "frac": 7, "fraction": [14, 17], "freedom": 16, "frequenc": [16, 20, 23], "friedman": 24, "from": [2, 3, 5, 6, 7, 8, 16, 26, 27, 28], "full": [2, 3, 4, 5, 6, 7], "func": 5, "function": [3, 7, 9, 10, 11, 13, 14, 15, 17, 19, 20, 23, 27], "fwer": [2, 5], "fwer_target": 2, "g": [2, 5, 27], "galleri": [2, 3, 4, 5, 6, 7, 28], "gamma": [6, 13, 17, 20], "gamma_min": [13, 17, 20], "gaonkar": [5, 12], "gap": [5, 16, 18, 24], "gaussian": [2, 5, 7, 16, 21, 22], "geer": [2, 16, 27], "gener": [1, 3, 4, 5, 6, 14, 16, 17, 20, 21, 22], "get": 3, "get_cmap": 4, "get_fdata": 5, "get_legend_handles_label": 7, "get_xaxi": 2, "get_yaxi": 2, "git": 27, "github": [2, 27], "give": 18, "given": [4, 7, 14, 16, 17, 18, 19, 20], "globerson": [4, 7, 9, 10], "go": [2, 3, 4, 5, 6, 7], "gold": [6, 21, 27], "good": 5, "gramfort": [18, 27], "greater": 2, "green": 7, "grei": 7, "grid": [23, 25], "grid_to_graph": [2, 5], "ground": [5, 7], "ground_truth_legend": 7, "group": [2, 4, 5, 9, 12, 14, 17, 18, 19, 27], "guarante": [2, 5], "gz": 5, "h": [2, 16, 27], "ha": [2, 4, 5, 6, 16], "hal": [6, 20], "handl": [7, 27], "hard": 5, "hardt": [4, 7, 9, 10], "have": [2, 5, 18, 27], "haxbi": 27, "haxby2001": 5, "haxby_dataset": 5, "header": 5, "heidelberg": [5, 12], "height": 7, "here": [5, 7, 27], "hidimstat": [2, 3, 4, 5, 6, 7], "hierarch": [14, 17], "high": [2, 4, 5, 6, 9, 13, 14, 16, 17, 19, 20, 21], "higher": 2, "highli": 4, "highlight": 7, "histgradientboostingregressor": 4, "hline": 6, "hochberg": 20, "hold": 2, "home": [4, 5], "hostedtoolcach": [5, 7], "hous": 5, "how": [7, 27], "howev": [2, 4, 5], "html": [6, 20, 27], "http": [2, 4, 5, 6, 7, 9, 10, 20, 27], "hyper": [2, 23, 25], "hypothesi": [16, 27], "i": [2, 3, 4, 5, 6, 7, 9, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26, 27], "idea": 2, "ideal": 27, "identifi": 7, "ie": [14, 17, 19, 23, 26], "iii": [6, 20], "iinfo": 6, "illustr": [2, 7, 27], "im": [2, 5], "imag": [2, 5, 12, 18, 27], "img": 5, "imp_cpi_linear": 7, "imp_cpi_non_linear": 7, "imp_pi_non_linear": 7, "impact": 4, "implement": [3, 9, 10, 11, 20], "import": [1, 8, 9, 10, 11, 27, 28], "importance_arr": 7, "importance_linear": 7, "importance_list": 7, "importance_non_linear": 7, "important_legend": 7, "important_pi": 7, "imputation_model": [4, 7, 9], "imshow": [2, 5], "inc": [4, 7, 9, 10], "includ": [5, 20], "increas": [5, 16, 20, 23], "inde": 2, "index": [7, 9, 20, 21], "infer": [6, 12, 14, 17, 19, 20, 21], "inference_method": 17, "infernec": 2, "influenc": 4, "inform": [4, 7, 9, 10, 18, 27], "input": [4, 20], "input_data": 5, "inria": [2, 27], "inspir": 7, "instanc": 7, "instead": 4, "int": [9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], "int32": 6, "integr": 4, "intellig": [9, 27], "intercept": 16, "interest": [4, 7, 16], "intern": [5, 6, 12, 20, 27], "interv": [16, 27], "intervent": [5, 12, 27], "introduc": [2, 4, 5, 6, 20], "introduct": 5, "intuit": 7, "invers": [5, 23], "inverse_transform": 5, "io": [2, 27], "ipynb": [2, 3, 4, 5, 6, 7], "isol": 5, "item": 7, "iter": [5, 16, 18, 20, 24], "its": [4, 5, 7], "j": [2, 5, 7, 14, 17, 18, 24, 27], "janson": [6, 21, 27], "jasa": 20, "javanmard": [2, 16, 27], "jerom": [6, 20], "jinchi": [6, 21], "job": [7, 9, 10, 11], "joblib": [7, 14, 16, 19, 20, 27], "joblib_verbos": 20, "joblib_versob": 20, "journal": [6, 13, 16, 20, 27], "jrsssb": 6, "jul": [6, 20], "juli": 4, "jupyt": [1, 2, 3, 4, 5, 6, 7], "k": [2, 4, 7, 9, 10], "kei": 3, "kernel": 7, "kf": 4, "kfold": [4, 18, 24], "kind": 27, "kneib": 4, "knockoff": [1, 8, 20, 21, 27, 28], "knockoff_aggreg": 6, "kwarg": [5, 14, 17, 19], "l": [4, 7, 13, 27], "label": [4, 5, 6, 7, 14, 17, 20], "labelbottom": 2, "labelleft": 2, "lack": [2, 7], "largest": 2, "largest_singular_valu": 12, "lasso": [1, 2, 5, 8, 14, 16, 17, 18, 19, 24, 27, 28], "lasso_cv": [20, 21], "lassocv": [18, 24], "lastli": 2, "latest": 27, "laur": 4, "layout": 6, "lead": 2, "leak": 7, "learn": [4, 6, 7, 9, 10, 11, 14, 16, 17, 20, 27], "learner": [1, 8, 28], "leav": 10, "ledoit_wolf": [20, 21], "ledoitwolf": 20, "left": [2, 7], "legend": [4, 6, 7], "len": 6, "length": [9, 18, 24], "leo": [4, 7], "less": 5, "let": 5, "level": [2, 4, 6, 9, 14, 16, 17, 19, 20, 21, 22, 23], "leverag": [2, 6], "levin": [4, 7, 9, 10], "lib": [5, 7], "like": 20, "limit": [2, 4], "linalg": 7, "line": [5, 7], "line2d": 7, "linear": [2, 3, 7, 14, 16, 17, 23, 25, 27], "linear_model": [4, 5, 7], "linestyl": 7, "linewidth": 3, "linkag": 2, "linspac": 7, "list": [9, 13, 20, 23, 25], "list_one_sided_pv": 13, "littl": 2, "load": 5, "load_diabet": 4, "loc": [6, 7], "local": 27, "loco_importance_list": 4, "loco_pv": 4, "loco_vim_arr": 4, "log10": 4, "log_": 4, "log_loss": 7, "logical_or": [2, 5], "logspac": [4, 7, 23, 25], "loki": 7, "lokybackend": 5, "look": 5, "loss": [4, 7, 9, 10, 11], "low": [16, 27], "lower": [2, 7, 16], "lowest": [13, 17], "luca": [6, 21], "luka": 20, "lv": [6, 21, 27], "lw": 7, "m": [4, 7, 9, 10, 16], "machin": [4, 6, 7, 16, 20, 27], "made": 4, "magnitud": 18, "mai": [5, 16], "make": [2, 7, 14, 16, 17, 19, 27], "mani": 5, "map": [2, 5, 12, 27], "mar": 9, "margin": 5, "marker": 7, "markers": 7, "mask": 5, "mask_img": 5, "mask_img_": 5, "masker": 5, "mass": 7, "match": 9, "math": 21, "matplotlib": [2, 3, 4, 6, 7, 27], "matplotlibdeprecationwarn": 4, "matrix": [2, 7, 14, 16, 17, 18, 19, 20, 21, 22], "matshow": 7, "max": 6, "max_it": [16, 18, 24], "maximum": [3, 16, 18, 24], "mb": [2, 3, 4, 5, 6, 7, 8, 28], "md": 5, "md5sum": 5, "mean": [4, 5, 7, 18, 24, 26], "mean_img": 5, "mean_vim": 4, "measur": [1, 8, 16, 20, 28], "median": [7, 17, 18], "medic": [5, 12, 27], "meg": [18, 27], "meier": [13, 20], "meinshausen": [13, 20], "mem": [8, 28], "memori": [2, 3, 4, 5, 6, 7, 14, 16, 17, 19, 20, 21], "messag": [14, 16, 17, 19, 20, 23], "method": [2, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 27], "methodologi": [6, 16, 27], "metric": [3, 4, 7], "might": 5, "mimic": 7, "min": 5, "mind": [2, 27], "minimum": 20, "minu": [14, 17, 19, 23, 26], "minut": [2, 3, 4, 5, 6, 7], "mline": 7, "mlr": [6, 20], "model": [2, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 21, 27], "model_linear": 7, "model_linear_c": 7, "model_non_linear": 7, "model_non_linear_c": 7, "model_select": [4, 7], "model_x_knockoff": 6, "moment": 26, "montanari": [16, 27], "more": [2, 5, 7, 20], "mse": 4, "much": [2, 5], "multi": [18, 27], "multipl": [2, 5, 6, 14, 17, 19, 20, 23, 27], "multitasklassocv": 18, "multivari": 7, "multivariate_1d_simul": 3, "multivariate_norm": 7, "multivariate_simul": 2, "must": [9, 10, 11, 18], "mx": 6, "mx_select": 6, "n": [3, 6, 13], "n_bootstrap": [5, 6, 17, 20], "n_cluster": [2, 5, 6, 14, 17], "n_featur": [2, 3, 5, 7, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], "n_fold": 4, "n_iter": [7, 13], "n_job": [2, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25], "n_permut": [4, 5, 7, 9, 11, 23], "n_sampl": [2, 3, 5, 7, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], "n_signal": 3, "n_split": [4, 7], "n_subject": 6, "n_time": [14, 17, 18, 19], "n_x": [2, 5], "n_y": [2, 5], "n_z": 5, "name": 4, "naumann": [4, 7, 9, 10], "nb": 6, "ncol": 3, "ndarrai": [12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26], "nearbi": 2, "neccessari": 27, "necessari": 2, "need": 27, "neg": [14, 17, 19, 23, 26], "neighbor": [2, 5, 22], "neural": [4, 7, 9, 10, 18, 27], "neurip": [4, 7, 9, 10, 18, 27], "neuroimag": [5, 27], "new": [4, 27], "next": 5, "nguyen": [2, 5, 6, 14, 17, 20, 27], "nguyen20a": [6, 20], "nicolai": 20, "niftimask": 5, "nii": 5, "nilearn": 5, "nilearn_data": 5, "nitrc": 5, "nodewis": 16, "nois": [2, 3, 7, 16, 18, 22, 24], "noise_i": 7, "nomin": 3, "non": [3, 4, 6, 7, 14, 16, 17, 19, 20, 23], "non_zero_index": 6, "none": [2, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26], "nonzero": 5, "norm": [4, 26], "normal": [6, 7, 26], "notabl": [2, 5, 6, 16], "note": [2, 16], "notebook": [1, 2, 3, 4, 5, 6, 7], "now": [2, 5, 27], "np": [2, 3, 4, 5, 6, 7, 23, 25], "nrow": 3, "nsubject": 6, "number": [2, 3, 4, 5, 6, 9, 10, 11, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25], "numer": [14, 17, 19, 23, 26], "numpi": [2, 3, 4, 5, 6, 7, 27], "nwith": 2, "object": [2, 7, 14, 16, 17, 18, 19, 20, 24], "observ": [3, 6], "obtain": [5, 7], "occur": 2, "octob": [4, 5, 7, 12], "off": 2, "offer": 5, "offset": [20, 21], "oh": [4, 7, 9, 10], "oj": 9, "one": [2, 4, 5, 7, 13, 14, 17, 19, 23, 26], "one_minus_pv": [2, 5, 14, 17, 19, 26], "one_minus_pval_ada_svr": 5, "one_minus_pval_cdl": 5, "one_minus_pval_corr": [2, 14, 17, 19, 23], "one_minus_pval_corr_ridge_perm_test": 5, "one_minus_pval_corr_svr_perm_test": 5, "one_minus_pval_ecdl": 5, "one_minus_pval_std_svr": 5, "one_sided_pv": 13, "ones": 4, "onli": [2, 4, 5, 16, 17, 26, 27], "opiton": 26, "oppos": 7, "opt": [5, 7], "optim": [2, 16, 18, 20, 21, 24, 27], "option": [12, 13, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26], "orang": 7, "order": 18, "org": [5, 6, 9, 27], "origin": [2, 5, 14, 16, 17], "orign": 5, "orlean": 27, "other": [5, 16], "otherwis": [9, 16, 18, 23], "oup": 6, "our": 27, "out": [5, 10], "outcom": [3, 4], "output": [5, 14, 16, 17, 19, 20], "over": [5, 6, 7], "p": [3, 5, 6, 13, 14, 16, 17, 19, 20, 23, 26, 27], "packag": [5, 7, 27], "pan": [6, 21, 27], "panda": [4, 5], "paper": [4, 7, 9, 10, 27], "paper_fil": [4, 7, 9, 10], "parallel": [5, 9, 10, 11, 14, 19, 20], "param_distribut": 7, "paramet": [5, 6, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27], "parametr": 5, "parcel": 5, "parralel": [16, 23], "partern": 5, "partit": [18, 24], "pass": [14, 17, 18, 19, 24], "patern": 5, "path": [14, 16, 17, 18, 19, 20, 24], "pattern": 5, "pd": [4, 5], "pdf": [4, 6, 7, 9, 10], "percentil": 20, "perform": [2, 3, 4, 9, 10, 11], "perm": 5, "permut": [5, 7, 9, 10, 11, 23, 27], "permutation_import": 4, "permutation_test": 5, "permutation_test_cv": 5, "permutationimport": [4, 7], "peter": 20, "php": [5, 9], "pi": [4, 7], "pi_importance_list": 4, "pi_non_linear": 7, "pi_pval": 4, "pi_vim_arr": 4, "pip": 27, "pleas": [2, 5], "plot": [6, 7], "plot_2d_simulation_exampl": [2, 8, 27, 28], "plot_dcrt_exampl": [3, 8, 28], "plot_diabetes_variable_importance_exampl": [4, 8, 28], "plot_fmri_data_exampl": [5, 8, 27, 28], "plot_knockoff_aggreg": [6, 8, 28], "plot_map": 5, "plot_meg_data_exampl": 27, "plot_result": 6, "plot_stat_map": 5, "plot_variable_importance_classif": [7, 8, 28], "plt": [2, 3, 4, 6, 7], "pmlr": [6, 20, 27], "poli": 7, "polynomi": 7, "popul": 7, "posit": [3, 7, 14, 17, 19, 23, 26], "possibl": 5, "potenti": 9, "power": [2, 3, 5, 6], "power_ev": 6, "power_mx": 6, "power_pv": 6, "powers_ev": 6, "powers_mx": 6, "powers_pv": 6, "pp": [5, 12, 27], "practic": 2, "precis": [2, 5], "precomput": 5, "predict": [2, 4, 5, 9, 10, 11], "predict_proba": [9, 10, 11], "preprint": [2, 14, 16, 17, 27], "preprocess_haxbi": 5, "prescal": 16, "present": [2, 5, 12], "preserv": 4, "press": [6, 20], "previou": 5, "previous": 5, "print": [3, 4, 14, 16, 17, 19, 20, 23], "problem": [2, 4, 5, 7, 16, 27], "procedur": [6, 12, 13, 18, 19, 20, 21, 24], "proceed": [4, 6, 7, 9, 10, 20, 27], "process": [2, 4, 6, 7, 9, 10, 18, 20, 27], "process_executor": 7, "produc": 5, "progress": [16, 20, 23], "project": 27, "projecteuclid": 27, "proport": 23, "provid": [2, 5, 9, 27], "pval": [2, 4, 5, 14, 17, 19, 20, 26], "pval_ada_svr": 5, "pval_arr": 7, "pval_cdl": 5, "pval_corr": [2, 14, 17, 19, 23], "pval_corr_ridge_perm_test": 5, "pval_corr_svr_perm_test": 5, "pval_ecdl": 5, "pval_from_cb": 2, "pval_from_scal": 5, "pval_std_svr": 5, "py": [2, 3, 4, 5, 6, 7, 8, 27, 28], "pymvpa": 5, "pyplot": [2, 3, 4, 6, 7], "pytest": 27, "python": [1, 2, 3, 4, 5, 6, 7], "python3": [5, 7], "qkad085": 6, "quantifi": 2, "quantil": [6, 7, 13, 17, 20], "quit": [2, 5], "r": [3, 4, 16, 24, 27], "r2_score": 4, "radiu": 2, "randint": 6, "randn": 7, "random": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 14, 17, 18, 20, 21, 24, 28], "random_st": [4, 6, 7, 9, 10, 11, 20], "randomforest": 3, "randomizedsearchcv": 7, "randomst": 7, "rang": [2, 3, 4, 6, 7, 16], "rate": [3, 6, 20, 21, 27], "rather": 5, "ratio": [3, 6], "ravel": 2, "rcond": 12, "rcparam": [3, 6], "read": 2, "read_csv": 5, "readabl": 5, "readm": 5, "real": 20, "realist": 5, "reason": [2, 5], "recommend": 2, "reconstruct": 4, "recov": [2, 5], "recoveri": [1, 8, 27, 28], "red": [4, 6], "reduc": [2, 5], "reduct": 2, "refer": [9, 10, 11, 12, 13, 14, 16, 17, 18, 20, 21, 24], "reflect": 4, "region": [2, 5, 16, 27], "regress": [2, 4, 13, 16, 18, 20, 24, 27], "regressor": 4, "regressor_list": 4, "regular": [5, 23, 25], "reid": 18, "relationship": [3, 4, 7], "relax": [2, 14, 17, 27], "relev": [2, 3, 5, 27], "relu": 3, "remain": [4, 5], "remov": 4, "ren": 6, "repetit": 3, "report": 20, "repres": 2, "request": 6, "requir": [2, 9, 27], "resampl": 5, "rescal": 7, "research": [6, 16, 20, 27], "reshap": [2, 20], "reshaping_funct": 20, "residu": [4, 16, 18], "residual_method": 16, "respons": 21, "result": 6, "results_forest": 3, "results_lasso": 3, "return": [2, 4, 5, 6, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], "rho": [3, 6, 22], "ridg": [4, 5], "ridgecv": [4, 7], "right": [6, 7], "rina": 6, "ritov": [16, 27], "rng": [6, 7], "roi_siz": 2, "roi_size_extend": 2, "root_mean_squared_error": [4, 9, 10, 11], "rotat": [6, 7], "rough": 2, "round": 2, "royal": [6, 16, 27], "rssb": 6, "run": [2, 3, 4, 5, 6, 7, 9, 10, 11, 23, 25, 27], "rune": [14, 17, 19], "runner": [4, 5], "saenko": [4, 7, 9, 10], "salmon": [2, 5, 14, 17, 18, 27], "same": [2, 17, 18], "sampl": [2, 4, 14, 17, 20, 22], "satisfi": 5, "scale": [5, 12, 16, 25], "scatter": [6, 7], "scenario": [2, 3], "scheme": [4, 20, 21], "scikit": [9, 10, 11, 14, 17, 27], "scipi": [4, 7, 27], "score": [4, 5, 7, 9, 10, 11, 20, 21, 23, 26], "screen": 3, "script": [7, 27], "sdp": [20, 21], "search": [23, 25], "second": [2, 3, 4, 5, 6, 7], "section": 2, "see": [2, 4, 5, 9], "seed": [2, 3, 5, 6, 7, 9, 10, 11, 14, 17, 18, 20, 21, 22, 23, 24], "seed_list": 6, "seem": [2, 5], "select": [2, 6, 20, 21, 27], "selected_cdl": 2, "selected_dl": 2, "selected_ecdl": 2, "self": 5, "sent": 20, "sep": 5, "seri": [6, 16, 27], "serv": [14, 17], "session": 5, "session_label": 5, "session_target": 5, "set": [2, 3, 4, 5, 9, 12, 23, 25, 27], "set_clim": 2, "set_tick": 4, "set_ticklabel": 4, "set_titl": [2, 3], "set_vis": 2, "set_xlabel": [4, 7], "set_xtick": 7, "set_xticklabel": [3, 4], "set_ylabel": [4, 7], "set_ylim": 3, "set_ytick": 7, "setp": 7, "sever": [17, 27], "sf": 4, "sform": 5, "shape": [2, 4, 5, 7, 12, 13, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26], "short": [5, 7], "shorter": 5, "shortli": 2, "should": [4, 5, 16], "show": [2, 3, 4, 5, 6], "shown": 5, "shrink": [20, 21], "shuffl": [4, 7, 22, 23], "side": [13, 26], "sigma": [2, 22], "sigma_hat": 24, "signal": 3, "signific": [4, 5, 12], "significantli": 2, "sim_ind": 3, "similarli": 2, "simpl": 18, "simpli": 7, "simu_data": 6, "simul": [1, 8, 27, 28], "sinc": [2, 5, 14, 16, 17], "singh": [6, 20], "singl": [4, 9, 27], "single_run": 6, "singular": 12, "sinica": 24, "site": [5, 7], "size": [2, 3, 6, 7, 22], "skip": 2, "sklearn": [2, 4, 5, 6, 7, 14, 17], "small": [2, 5, 12], "smaller": [2, 12, 16, 18, 24], "smooth": 2, "smooth_x": 2, "smoothing_fwhm": 5, "snr": 3, "so": 2, "societi": [6, 16, 27], "solut": [2, 4, 5, 17], "solv": 27, "some": [2, 5, 7], "sourc": [1, 2, 3, 4, 5, 6, 7, 18, 27], "space": [2, 4, 5], "spars": 20, "sparsifi": 27, "sparsiti": 6, "spatial": [2, 5, 14, 17, 27], "spatio": [18, 27], "specif": 7, "specifi": 7, "sphinx": [1, 2, 3, 4, 5, 6, 7], "sphinx_bootstrap_them": 27, "sphinx_galleri": 27, "split": [4, 7], "springer": [5, 12, 27], "spuriou": [5, 7], "squar": 2, "srt": 20, "stack": 7, "stand": 5, "standard": [2, 4, 5, 7, 12, 18, 20, 21, 22, 24, 25], "standardized_svr": 5, "star": 7, "stat": [4, 7, 20, 21, 23], "stat_tool": [2, 5], "stationari": 18, "statist": [2, 3, 4, 5, 6, 7, 9, 10, 12, 13, 14, 16, 17, 18, 19, 20, 21], "statistica": 24, "std": [4, 7], "std_vim": 4, "stdout": 20, "step": [5, 14, 18, 19], "still": 2, "stop": 7, "str": [9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 26], "stratifiedkfold": 7, "strength": 23, "string": [14, 16, 17, 19, 20], "strobl": 4, "structur": [2, 5, 7, 22, 27], "studi": 24, "sub": [2, 4], "subj2": 5, "subplot": [2, 3, 4, 7], "subsampl": [14, 17], "subset": 4, "substitut": 4, "suitabl": 5, "sum": [2, 3], "summari": 2, "support": [1, 7, 8, 9, 10, 11, 22, 27, 28], "support_s": [3, 22], "surviv": [5, 13, 23], "svc": 7, "svm": [5, 7, 12], "svr": [5, 23, 25], "svr_permutation_test_infer": 5, "sylvain": [6, 20], "sym": 6, "system": [4, 7, 9, 10, 18, 27], "t": [2, 4, 5, 7, 9, 10, 14, 17, 27], "tab": [4, 7], "tab10": 4, "tackl": 27, "take": [2, 5, 18], "tar": 5, "target": [2, 4, 5, 7, 12, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25], "target_fw": 5, "task": [5, 18, 27], "tck_id": 7, "techniqu": [2, 5], "tempor": [14, 17, 18, 19, 27], "term": 7, "termin": 27, "test": [1, 2, 5, 7, 8, 14, 16, 17, 19, 20, 21, 23, 27, 28], "test_index": 4, "test_scor": 21, "text": [4, 7], "than": [2, 5, 7, 12, 16, 18, 20, 24], "thank": [2, 5], "thei": [4, 5], "them": 2, "theoret": [2, 5], "therefor": [4, 7], "thi": [7, 14, 16, 17, 18, 20, 24, 27], "thin": 2, "third": 7, "thirion": [2, 4, 5, 6, 7, 9, 10, 14, 17, 18, 20, 27], "thoma": 4, "those": [2, 5], "thr_c": 2, "thr_nc": 2, "thre": 21, "three": 27, "thresh": 5, "threshold": [5, 7, 20, 21], "through": [4, 7, 9, 10, 27], "thu": [4, 5], "tibshirani": 24, "tick": 4, "tick_param": 2, "tight_layout": 2, "time": [2, 3, 4, 5, 6, 7, 17, 18], "timeout": 7, "titl": [2, 4, 5, 6], "tm08647": 20, "to_numpi": 5, "toeplitz": [7, 22], "tol": [16, 18, 24], "toler": [2, 5, 16, 18, 24], "too": [5, 7], "top": 2, "total": [2, 3, 4, 5, 6, 7, 8, 28], "toward": 4, "train": 7, "train_index": 4, "train_siz": [2, 14, 17], "transform": [9, 10, 11], "translat": [2, 5], "tresh": 5, "true": [2, 3, 4, 5, 6, 7, 16, 18, 20, 21, 22], "truli": 4, "truth": 7, "try": 5, "ttest_1samp": 7, "tuan": [6, 20], "two": [2, 4, 5, 6, 7, 14, 17, 18, 19], "type": [2, 3, 4, 5, 26], "typei_error": 3, "u": [5, 27], "uncertainti": 2, "uncompress": [5, 14, 17], "under": [4, 7, 20], "underli": 26, "unecessari": 16, "uniqu": [4, 5], "unlik": 2, "unstabl": 6, "until": [16, 18, 24], "up": 19, "updat": [3, 6, 16, 18, 24], "upper": [7, 16], "url": [4, 6, 7, 9, 10, 20], "us": [1, 2, 5, 6, 7, 8, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 28], "usa": 27, "usag": [2, 3, 4, 5, 6, 7], "userwarn": [4, 5, 7], "util": [5, 6], "v": [1, 5, 8, 28], "v119": [6, 20], "v38i10": 9, "val": [23, 25], "valid": [4, 7, 9, 10, 18, 23, 24, 25, 27], "valu": [3, 5, 6, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 23, 25, 26], "van": [2, 16, 27], "vancouv": 27, "var": 4, "variabl": [1, 3, 6, 8, 9, 10, 20, 21, 27, 28], "varianc": 24, "variant": 4, "varoquaux": [5, 27], "vector": [2, 7, 12, 14, 16, 17, 19, 20, 21, 22, 24, 25], "verbos": [3, 14, 16, 17, 19, 20, 21, 23], "veri": 5, "version": [4, 20, 27], "vert": 7, "via": 27, "vienna": 27, "view": 9, "vim": 4, "visibl": 2, "visual": 5, "volum": [4, 6, 7, 9, 10, 20], "voxel": 5, "w": 2, "wa": [2, 4], "walker": 18, "want": [5, 27], "ward": [2, 5, 14, 17], "warn": [5, 7], "we": [2, 4, 5, 6, 7, 14, 17, 19, 27], "wei": 16, "weight": [2, 5, 7], "weight_map_2d_extend": 2, "well": 7, "were": 7, "when": [2, 4, 5, 16, 23], "where": [4, 5, 7], "whether": [20, 21], "which": [2, 4, 5, 7, 18, 24], "while": [4, 7], "whisker": 7, "white": [2, 22], "width": [4, 7], "without": 2, "work": [4, 5, 27], "worker": [5, 7, 20], "would": 27, "wrap": [5, 19], "www": 5, "x": [2, 3, 4, 5, 6, 7, 12, 16, 18, 19, 20, 21, 22, 23, 24, 25, 27], "x1": 7, "x10": 7, "x2": 7, "x4": 7, "x6": 7, "x64": [5, 7], "x8": 7, "x9": 7, "x_init": [2, 14, 17], "x_test": 4, "x_tild": 21, "x_train": 4, "xmax": 6, "xmin": 6, "xtick": 6, "y": [2, 3, 4, 5, 6, 7, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27], "y_cont": 7, "y_pred": 4, "y_test": 4, "y_train": 4, "y_true": 4, "yekuti": 20, "yingi": [6, 21], "ylabel": 6, "yoav": 20, "you": [2, 5, 16, 27], "ytick": 7, "yule": 18, "z": [5, 26], "zeilei": 4, "zero": [2, 6, 7, 12, 14, 16, 17, 19, 20, 23, 26], "zhang": [2, 16, 27], "zhimei": 6, "zip": [1, 2, 3, 4, 5, 6, 7], "zorder": 7, "zscore": [2, 5, 26], "zscore_from_pv": [2, 5], "zscore_img": 5, "zscore_threshold": 5, "zscore_threshold_clust": 5, "zscore_threshold_corr": 5, "zscore_threshold_no_clust": 5}, "titles": ["API Documentation", "Examples Gallery", "Support recovery on simulated data (2D)", "Distilled Conditional Randomization Test (dCRT) using Lasso vs Random Forest learners", "Variable Importance on diabetes dataset", "Support recovery on fMRI data", "Knockoff aggregation on simulated data", "Measuring variable importance in classification", "Computation times", "hidimstat.CPI", "hidimstat.LOCO", "hidimstat.PermutationImportance", "hidimstat.ada_svr", "hidimstat.aggregate_quantiles", "hidimstat.clustered_inference", "hidimstat.data_simulation", "hidimstat.desparsified_lasso", "hidimstat.ensemble_clustered_inference", "hidimstat.group_reid", "hidimstat.hd_inference", "hidimstat.knockoff_aggregation", "hidimstat.model_x_knockoff", "hidimstat.multivariate_1D_simulation", "hidimstat.permutation_test_cv", "hidimstat.reid", "hidimstat.standardized_svr", "hidimstat.zscore_from_pval", "HiDimStat: High-dimensional statistical inference tool for Python", "Computation times"], "titleterms": {"2d": 2, "ada_svr": 12, "aggreg": 6, "aggregate_quantil": 13, "algorithm": [2, 5], "analysi": [2, 5], "analyz": 4, "api": [0, 27], "baselien": 4, "baselin": 4, "build": 27, "choos": 2, "class": 0, "classif": 7, "cluster": 5, "clustered_infer": 14, "comparison": 3, "comput": [2, 3, 4, 7, 8, 28], "condit": 3, "cpi": [4, 9], "data": [2, 5, 6, 7], "data_simul": 15, "dataset": [4, 5], "dcrt": 3, "defin": 4, "depend": 27, "desparsified_lasso": 16, "diabet": 4, "dimension": 27, "distil": 3, "document": [0, 27], "ensemble_clustered_infer": 17, "estim": [0, 2], "exampl": [1, 27], "featureagglomer": 5, "fetch": 5, "fit": 4, "fmri": 5, "forest": 3, "from": 4, "function": [0, 2, 4, 5], "galleri": 1, "gather": 5, "gener": [2, 7], "given": 5, "group_reid": 18, "haxbi": 5, "hd_infer": 19, "hidimstat": [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27], "high": 27, "import": [2, 3, 4, 5, 6, 7], "infer": [2, 5, 7, 27], "initi": 5, "instal": 27, "knockoff": 6, "knockoff_aggreg": 20, "lasso": 3, "learner": 3, "load": 4, "loco": [4, 10], "main": 27, "make": 5, "measur": [4, 7], "method": 4, "model": 4, "model_x_knockoff": 21, "multivariate_1d_simul": 22, "need": [2, 3, 4, 5, 6, 7], "object": 5, "other": 27, "p": [4, 7], "paramet": 2, "perform": 5, "permut": 4, "permutation_test_cv": 23, "permutationimport": 11, "plot": [2, 3, 5], "preprocess": 5, "process": 3, "python": 27, "random": 3, "recoveri": [2, 5], "refer": [2, 4, 5, 6, 7, 27], "reid": 24, "result": [2, 4, 5], "score": 2, "script": [2, 3, 4, 5, 6], "sever": [2, 5], "simul": [2, 6], "specif": 2, "standardized_svr": 25, "statist": 27, "subject": 5, "support": [2, 5], "test": 3, "thi": [2, 3, 4, 5, 6], "threshold": 2, "time": [8, 28], "tool": 27, "us": [3, 4, 27], "v": 3, "valu": [4, 7], "variabl": [4, 7], "visual": 7, "z": 2, "zscore_from_pv": 26}})
\ No newline at end of file
+Search.setIndex({"alltitles": {"API": [[27, "api"]], "API Documentation": [[0, null]], "Analysis of the results": [[2, "analysis-of-the-results"], [5, "analysis-of-the-results"]], "Analyze the results": [[4, "analyze-the-results"]], "Build the documentation": [[27, "build-the-documentation"]], "Choosing inference parameters": [[2, "choosing-inference-parameters"]], "Classes": [[0, "classes"]], "Computation times": [[8, null], [28, null]], "Compute the p-values for the variable importance": [[7, "compute-the-p-values-for-the-variable-importance"]], "Computing z-score thresholds for support estimation": [[2, "computing-z-score-thresholds-for-support-estimation"]], "Define a function to compute the p-value from importance values": [[4, "define-a-function-to-compute-the-p-value-from-importance-values"]], "Dependencies": [[27, "dependencies"]], "Distilled Conditional Randomization Test (dCRT) using Lasso vs Random Forest learners": [[3, null]], "Documentation & Examples": [[27, "documentation-examples"]], "Estimators": [[0, "estimators"]], "Examples Gallery": [[1, null]], "Fit a baselien model on the diabetes dataset": [[4, "fit-a-baselien-model-on-the-diabetes-dataset"]], "Fit a baseline model on the diabetes dataset": [[4, "fit-a-baseline-model-on-the-diabetes-dataset"]], "Function to fetch and preprocess Haxby dataset": [[5, "function-to-fetch-and-preprocess-haxby-dataset"]], "Functions": [[0, "functions"]], "Gathering and preprocessing Haxby dataset for a given subject": [[5, "gathering-and-preprocessing-haxby-dataset-for-a-given-subject"]], "Generate the data": [[7, "generate-the-data"]], "Generating the data": [[2, "generating-the-data"]], "HiDimStat: High-dimensional statistical inference tool for Python": [[27, null]], "Imports needed": [[7, "imports-needed"]], "Imports needed for this script": [[2, "imports-needed-for-this-script"], [3, "imports-needed-for-this-script"], [4, "imports-needed-for-this-script"], [5, "imports-needed-for-this-script"], [6, "imports-needed-for-this-script"]], "Inference with several algorithms": [[2, "inference-with-several-algorithms"]], "Initializing FeatureAgglomeration object that performs the clustering": [[5, "initializing-featureagglomeration-object-that-performs-the-clustering"]], "Installation": [[27, "installation"]], "Knockoff aggregation on simulated data": [[6, null]], "Load the diabetes dataset": [[4, "load-the-diabetes-dataset"]], "Main references": [[27, "main-references"]], "Making the inference with several algorithms": [[5, "making-the-inference-with-several-algorithms"]], "Measure the importance of variables using the CPI method": [[4, "measure-the-importance-of-variables-using-the-cpi-method"]], "Measure the importance of variables using the LOCO method": [[4, "measure-the-importance-of-variables-using-the-loco-method"]], "Measure the importance of variables using the permutation method": [[4, "measure-the-importance-of-variables-using-the-permutation-method"]], "Measuring variable importance in classification": [[7, null]], "Other useful references": [[27, "other-useful-references"]], "Plotting the comparison": [[3, "plotting-the-comparison"]], "Plotting the results": [[5, "plotting-the-results"]], "Processing the computations": [[3, "processing-the-computations"]], "References": [[2, "references"], [4, "references"], [5, "references"], [6, "references"], [7, "references"], [27, "references"]], "Results": [[2, "results"]], "Specific plotting functions": [[2, "specific-plotting-functions"]], "Support recovery on fMRI data": [[5, null]], "Support recovery on simulated data (2D)": [[2, null]], "Variable Importance on diabetes dataset": [[4, null]], "Variable importance inference": [[7, "variable-importance-inference"]], "Visualize the data": [[7, "visualize-the-data"]], "Visualize the variable importance": [[7, "visualize-the-variable-importance"]], "hidimstat.CPI": [[9, null]], "hidimstat.LOCO": [[10, null]], "hidimstat.PermutationImportance": [[11, null]], "hidimstat.ada_svr": [[12, null]], "hidimstat.aggregate_quantiles": [[13, null]], "hidimstat.clustered_inference": [[14, null]], "hidimstat.data_simulation": [[15, null]], "hidimstat.desparsified_lasso": [[16, null]], "hidimstat.ensemble_clustered_inference": [[17, null]], "hidimstat.group_reid": [[18, null]], "hidimstat.hd_inference": [[19, null]], "hidimstat.knockoff_aggregation": [[20, null]], "hidimstat.model_x_knockoff": [[21, null]], "hidimstat.multivariate_1D_simulation": [[22, null]], "hidimstat.permutation_test_cv": [[23, null]], "hidimstat.reid": [[24, null]], "hidimstat.standardized_svr": [[25, null]], "hidimstat.zscore_from_pval": [[26, null]]}, "docnames": ["api", "auto_examples/index", "auto_examples/plot_2D_simulation_example", "auto_examples/plot_dcrt_example", "auto_examples/plot_diabetes_variable_importance_example", "auto_examples/plot_fmri_data_example", "auto_examples/plot_knockoff_aggregation", "auto_examples/plot_variable_importance_classif", "auto_examples/sg_execution_times", "generated/hidimstat.CPI", "generated/hidimstat.LOCO", "generated/hidimstat.PermutationImportance", "generated/hidimstat.ada_svr", "generated/hidimstat.aggregate_quantiles", "generated/hidimstat.clustered_inference", "generated/hidimstat.data_simulation", "generated/hidimstat.desparsified_lasso", "generated/hidimstat.ensemble_clustered_inference", "generated/hidimstat.group_reid", "generated/hidimstat.hd_inference", "generated/hidimstat.knockoff_aggregation", "generated/hidimstat.model_x_knockoff", "generated/hidimstat.multivariate_1D_simulation", "generated/hidimstat.permutation_test_cv", "generated/hidimstat.reid", "generated/hidimstat.standardized_svr", "generated/hidimstat.zscore_from_pval", "index", "sg_execution_times"], "envversion": {"sphinx": 64, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinxcontrib.bibtex": 9}, "filenames": ["api.rst", "auto_examples/index.rst", "auto_examples/plot_2D_simulation_example.rst", "auto_examples/plot_dcrt_example.rst", "auto_examples/plot_diabetes_variable_importance_example.rst", "auto_examples/plot_fmri_data_example.rst", "auto_examples/plot_knockoff_aggregation.rst", "auto_examples/plot_variable_importance_classif.rst", "auto_examples/sg_execution_times.rst", "generated/hidimstat.CPI.rst", "generated/hidimstat.LOCO.rst", "generated/hidimstat.PermutationImportance.rst", "generated/hidimstat.ada_svr.rst", "generated/hidimstat.aggregate_quantiles.rst", "generated/hidimstat.clustered_inference.rst", "generated/hidimstat.data_simulation.rst", "generated/hidimstat.desparsified_lasso.rst", "generated/hidimstat.ensemble_clustered_inference.rst", "generated/hidimstat.group_reid.rst", "generated/hidimstat.hd_inference.rst", "generated/hidimstat.knockoff_aggregation.rst", "generated/hidimstat.model_x_knockoff.rst", "generated/hidimstat.multivariate_1D_simulation.rst", "generated/hidimstat.permutation_test_cv.rst", "generated/hidimstat.reid.rst", "generated/hidimstat.standardized_svr.rst", "generated/hidimstat.zscore_from_pval.rst", "index.rst", "sg_execution_times.rst"], "indexentries": {"__init__() (hidimstat.cpi method)": [[9, "hidimstat.CPI.__init__", false]], "__init__() (hidimstat.loco method)": [[10, "hidimstat.LOCO.__init__", false]], "__init__() (hidimstat.permutationimportance method)": [[11, "hidimstat.PermutationImportance.__init__", false]], "ada_svr() (in module hidimstat)": [[12, "hidimstat.ada_svr", false]], "aggregate_quantiles() (in module hidimstat)": [[13, "hidimstat.aggregate_quantiles", false]], "clustered_inference() (in module hidimstat)": [[14, "hidimstat.clustered_inference", false]], "cpi (class in hidimstat)": [[9, "hidimstat.CPI", false]], "desparsified_lasso() (in module hidimstat)": [[16, "hidimstat.desparsified_lasso", false]], "ensemble_clustered_inference() (in module hidimstat)": [[17, "hidimstat.ensemble_clustered_inference", false]], "group_reid() (in module hidimstat)": [[18, "hidimstat.group_reid", false]], "hd_inference() (in module hidimstat)": [[19, "hidimstat.hd_inference", false]], "hidimstat.data_simulation": [[15, "module-hidimstat.data_simulation", false]], "knockoff_aggregation() (in module hidimstat)": [[20, "hidimstat.knockoff_aggregation", false]], "loco (class in hidimstat)": [[10, "hidimstat.LOCO", false]], "model_x_knockoff() (in module hidimstat)": [[21, "hidimstat.model_x_knockoff", false]], "module": [[15, "module-hidimstat.data_simulation", false]], "multivariate_1d_simulation() (in module hidimstat)": [[22, "hidimstat.multivariate_1D_simulation", false]], "permutation_test_cv() (in module hidimstat)": [[23, "hidimstat.permutation_test_cv", false]], "permutationimportance (class in hidimstat)": [[11, "hidimstat.PermutationImportance", false]], "reid() (in module hidimstat)": [[24, "hidimstat.reid", false]], "standardized_svr() (in module hidimstat)": [[25, "hidimstat.standardized_svr", false]], "zscore_from_pval() (in module hidimstat)": [[26, "hidimstat.zscore_from_pval", false]]}, "objects": {"hidimstat": [[9, 0, 1, "", "CPI"], [10, 0, 1, "", "LOCO"], [11, 0, 1, "", "PermutationImportance"], [12, 2, 1, "", "ada_svr"], [13, 2, 1, "", "aggregate_quantiles"], [14, 2, 1, "", "clustered_inference"], [15, 3, 0, "-", "data_simulation"], [16, 2, 1, "", "desparsified_lasso"], [17, 2, 1, "", "ensemble_clustered_inference"], [18, 2, 1, "", "group_reid"], [19, 2, 1, "", "hd_inference"], [20, 2, 1, "", "knockoff_aggregation"], [21, 2, 1, "", "model_x_knockoff"], [22, 2, 1, "", "multivariate_1D_simulation"], [23, 2, 1, "", "permutation_test_cv"], [24, 2, 1, "", "reid"], [25, 2, 1, "", "standardized_svr"], [26, 2, 1, "", "zscore_from_pval"]], "hidimstat.CPI": [[9, 1, 1, "", "__init__"]], "hidimstat.LOCO": [[10, 1, 1, "", "__init__"]], "hidimstat.PermutationImportance": [[11, 1, 1, "", "__init__"]]}, "objnames": {"0": ["py", "class", "Python class"], "1": ["py", "method", "Python method"], "2": ["py", "function", "Python function"], "3": ["py", "module", "Python module"]}, "objtypes": {"0": "py:class", "1": "py:method", "2": "py:function", "3": "py:module"}, "terms": {"": [2, 4, 7, 9, 10, 16, 24, 27], "0": [2, 3, 4, 5, 6, 7, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24], "00": [8, 23, 25, 28], "0001": [18, 24], "001": [12, 16], "01": [5, 6, 8, 16, 18, 23, 24, 25, 28], "01492149527525": 4, "02": [23, 25], "02351": 21, "02590": [2, 14, 17, 27], "03": [23, 25], "04": [23, 25], "044": [2, 8, 28], "05": [4, 6, 7, 8, 20, 23, 25, 28], "06": [23, 25], "07": [8, 23, 25, 28], "08": [8, 20, 28], "08885": 16, "09": [6, 8, 28], "0x7fcb2945d6d0": 7, "0x7fcb297d8b00": 7, "0x7fcb297daf90": 7, "0x7fcb297db2c0": 7, "0x7fcb299c8170": 7, "0x7fcb299c8cb0": 7, "0x7fcb299c8e90": 7, "0x7fcb299c90a0": 7, "0x7fcb299c9ca0": 7, "0x7fcb299cbef0": 7, "0x7fcc17b51370": 7, "1": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28], "10": [2, 3, 4, 5, 6, 7, 9, 20, 22, 27], "100": [2, 5, 22], "1000": [3, 23], "10000": [18, 24], "1010933404324": [4, 7], "1013699998": 20, "1023": [4, 7], "104": [13, 20], "1093": 6, "11": [2, 4], "110182400": 5, "1111": 6, "11195": 9, "11203": 9, "1166": [16, 27], "117": [5, 8, 28], "117921": [5, 27], "1186": 4, "119": [6, 20, 27], "1198": 20, "12": [2, 5, 7], "1202": [16, 27], "1214": [20, 27], "122": 6, "12265": 6, "13": [2, 6, 20], "13716": 16, "14": [2, 5], "1438606853": 27, "1471": 4, "15": [2, 3, 5, 16, 27], "151600911163946": 4, "154": 6, "16": 2, "1609": 9, "1610": 21, "1671": [13, 20], "1681": [13, 20], "17": 2, "18": [2, 6, 20], "19": 2, "1902": 16, "199": 5, "1d": [20, 21, 22], "1e": [4, 12, 16, 18, 24], "1e4": [18, 24], "2": [2, 3, 4, 5, 6, 7, 8, 9, 13, 16, 17, 18, 20, 24, 28], "20": [2, 5, 6, 7], "200": [2, 5], "2001": [4, 7, 20], "2007": 16, "2008": 4, "2009": [13, 20], "2010": 5, "2012": [5, 12], "2014": [2, 16, 27], "2015": 27, "2016": 24, "2017": 21, "2018": [6, 27], "2019": 16, "2020": [6, 16, 18, 20, 27], "2021": [2, 5, 14, 17, 27], "2023": [4, 6, 7, 9, 10, 27], "2024": [9, 27], "2055": 27, "2085": 27, "21": [2, 3], "2105": 4, "2106": [2, 14, 17, 27], "21600000000000003": 5, "217": [16, 27], "22": 2, "23": 2, "234": [5, 27], "24": 2, "240": 4, "242": [16, 27], "249692160": 5, "25": [5, 6, 7, 8, 17, 20, 28], "256": 4, "26": 6, "26090648721779": 4, "27": [6, 8, 28], "271": [4, 8, 28], "2722061930940729": 4, "2869": [16, 27], "287948367546456": 4, "289": [7, 8, 28], "28997": 9, "29": 20, "2909": [16, 27], "291168628": 5, "2d": [1, 8, 21, 27, 28], "3": [2, 3, 4, 5, 6, 7, 12, 16, 17, 20, 27], "30": 7, "307": 4, "308": 5, "3119253313517": 4, "32": [4, 7], "33": 5, "33092885980301545": 4, "33374807702299": 4, "3348": [8, 28], "3349": 5, "34873505091371093": 4, "34h": 18, "34th": 27, "35": 24, "352999936251216": 4, "35323376775815": 4, "36": [4, 7, 9, 10], "3633702441001": 4, "36967014548640154": 4, "37": 5, "37th": [6, 20, 27], "38": 9, "38th": 27, "4": [2, 3, 4, 5, 7, 16, 18, 24], "40": [2, 5, 7], "400": 7, "42": [16, 27], "43": [7, 8, 27, 28], "443": [6, 8, 28], "45": [4, 6, 7], "46114740610001137": 4, "46246416851449": 4, "47": 4, "479244269131684": 4, "48683083150894546": 4, "488": [13, 20], "49": [4, 5], "492": 5, "49274696": 6, "5": [2, 3, 4, 5, 6, 7, 16, 20, 27], "50": [4, 5, 7, 9, 11, 20], "500": [5, 6, 22], "5000": 16, "5048253747874585": 4, "51": 4, "52": [4, 8, 28], "5235794267120801": 4, "53": 4, "5316220308691071": 4, "5333394029342122": 4, "54": 4, "55": 4, "551": [6, 27], "5514585816057873": 4, "56": 4, "56629998": 6, "57429457038258": 4, "577": [6, 27], "58": 4, "5858181205553151": 4, "59": 4, "5979566135054368": 4, "5e": 3, "6": [2, 3, 4, 5, 7, 8, 27, 28], "61": 4, "621": [8, 28], "622": 7, "626": [4, 8, 28], "638": 27, "643": [3, 8, 28], "646": 27, "65": 6, "665318862395647": 4, "666537166030764": 4, "67": 24, "67662": [4, 7, 9, 10], "67685": [4, 7, 9, 10], "683": 5, "69518424561582": 4, "7": [2, 3, 4, 5, 6, 7, 23, 25], "704": [8, 28], "705": 2, "723": [5, 12], "7236176985951": 4, "7283": [6, 20], "7293": [6, 20], "730": [5, 12], "74": 7, "7422256933791083": 5, "752": 7, "75372711094103": 4, "764": [3, 8, 28], "769": [6, 8, 28], "7868": 5, "8": [2, 3, 4, 5, 7, 8, 28], "80": [6, 7, 27], "85": 5, "86": 6, "9": [2, 3, 4, 8, 23, 25, 28], "90": 7, "927": [8, 28], "95": 16, "A": [2, 4, 5, 6, 7, 9, 10, 14, 16, 17, 18, 24, 27], "And": 7, "As": [2, 5, 27], "By": [5, 14, 16, 17, 19, 20], "For": [2, 5, 27], "If": [2, 9, 14, 16, 17, 18, 19, 20, 23, 27], "In": [2, 4, 5, 6, 7, 9, 10, 12, 18, 20, 27], "It": 5, "On": [16, 27], "One": [10, 14, 17, 19, 23, 26], "Or": 27, "The": [2, 3, 4, 5, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 23, 24, 25, 27], "Then": [2, 16], "To": [2, 4, 5, 7, 27], "_": [2, 3, 4, 5, 6], "_3": 6, "_551": 6, "_80": 6, "__": 3, "__init__": [9, 10, 11], "_coordinate_desc": 5, "_map_show": 5, "_slicer": 5, "aaai": [9, 27], "aarti": [6, 20], "ab": 7, "about": [2, 27], "abov": 20, "academ": 6, "accept": 26, "accord": 5, "account": 2, "accur": [2, 14, 17, 19, 23, 26], "achim": 4, "activ": [2, 5], "ad": 5, "ada": 5, "ada_svr": 5, "adapt": [5, 13, 17, 20], "adaptive_aggreg": 20, "adaptive_permutation_threshold": 5, "add": [2, 5], "add_one_subplot": 2, "addit": [2, 5, 16, 22], "adjust": [5, 16], "advanc": [4, 7, 9, 10, 27], "advantag": 2, "advoc": 5, "affect": 4, "aforement": 27, "after": [2, 4], "ag": 7, "against": [16, 18], "aggreg": [1, 2, 5, 8, 13, 17, 20, 27, 28], "aggregated_ev": 20, "aggregated_ko_select": 6, "aggregated_pv": 20, "agnost": [4, 7], "ahmad": [4, 7, 9, 10], "aim": [2, 4, 5], "ako": 27, "al": [2, 4, 5, 6, 7, 9, 10, 12, 20, 21], "alexi": [6, 20], "algorithm": [9, 10, 14, 17, 27], "all": [1, 5, 14, 16, 17, 20, 28], "allow": 5, "along": 20, "alpha": [3, 4, 6, 7, 16], "alpha_max": [16, 18, 24], "alpha_max_fract": 16, "alpha_min": [18, 24], "alreadi": 5, "also": [2, 4, 5, 7, 16, 18, 27], "alwai": 16, "american": [13, 20], "among": [2, 5], "an": [2, 4, 6], "anat": 5, "anatom": 5, "ani": [4, 5], "ann": [4, 20], "annal": [16, 27], "anoth": 5, "ao": [20, 27], "aos1337": 27, "append": [2, 3, 4, 6, 7], "appli": [2, 3, 5, 20], "applic": [16, 27], "appreci": 27, "approach": 4, "approxim": 5, "ar": [2, 3, 4, 5, 7, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 23, 24, 27], "arang": [4, 7], "argu": 2, "argument": [14, 17, 19], "arlot": [6, 20, 27], "around": 5, "arrai": [4, 7, 12, 16, 20, 21, 23, 24, 25], "articl": [6, 9, 27], "artifici": [9, 27], "arxiv": [2, 6, 14, 16, 17, 21, 27], "asarrai": 5, "assess": [4, 7, 9, 10, 27], "assist": [5, 12, 27], "associ": [4, 6, 7, 9, 10, 13, 20, 27], "assum": [5, 26], "astyp": 5, "asymptot": [16, 27], "augustin": 4, "austria": 27, "auto_exampl": 8, "auto_examples_jupyt": 1, "auto_examples_python": 1, "autoregress": 18, "avail": [2, 14, 16, 17, 19, 27], "averag": 2, "avoid": 16, "ax": [2, 3, 4, 7], "axhlin": [3, 4], "axi": [2, 4, 7], "axvlin": 7, "b": [2, 5, 6, 7, 12, 14, 16, 17, 18, 27], "back": 5, "backend": 5, "bar": 4, "barber": [6, 27], "base": [3, 4, 5, 7, 12, 21], "becaus": 7, "been": [16, 27], "befor": [4, 14, 17, 19, 20, 21], "beforehand": 16, "behavior": 5, "being": [13, 17], "bellec": 16, "below": [2, 5], "benefit": [2, 5, 7], "benjamini": 20, "berlin": [5, 12], "bertrand": [4, 6, 7, 9, 10, 20], "best": 6, "beta": [2, 22], "beta_1": 7, "beta_2": 7, "beta_3": 7, "beta_extend": 2, "beta_hat": [2, 5, 12, 14, 16, 17, 18, 19, 24, 25], "better": 5, "between": [2, 4, 5, 7, 18, 22], "bg_img": 5, "bh": 20, "bhq": 20, "bhy": 20, "bias": [4, 16, 27], "binari": 7, "binh": [6, 20], "bioinformat": 4, "bisect": 4, "bit": 2, "black": 7, "blue": [6, 7], "bmc": 4, "bmi": 7, "bodi": 7, "bonferroni": [2, 5], "bool": [5, 16, 18, 20, 21, 22], "bootstrap": 20, "both": [2, 4], "bottom": 2, "boulesteix": 4, "bound": [2, 6, 16], "box": 7, "box1": 7, "boxplot": [3, 6, 7], "brain": 5, "break": [2, 4, 22], "breiman": [4, 7], "briefli": 2, "buid": 4, "build": [2, 5, 14, 17], "bunch": 5, "bypass": 4, "byte": 5, "b\u00fchlmann": [13, 16, 20, 27], "c": [2, 5, 6, 7, 12, 16, 23, 25, 27], "cach": [14, 16, 17, 19, 20], "cal_fdp_pow": 6, "calcul": [20, 21], "call": [2, 5], "callabl": [9, 10, 11], "can": [2, 5, 6, 7, 9, 27], "canada": 27, "cand": 21, "cand\u00e8": [6, 27], "cap": 7, "captur": 7, "carolin": 4, "case": [2, 4], "caus": 7, "cb_max": [2, 16], "cb_min": [2, 16], "cc": [4, 7, 9, 10], "cd": 27, "cd_fast": 5, "cdot": 7, "celentano": 16, "center": [16, 20, 21], "cf": [13, 16], "cham": 27, "chamma": [4, 7, 9, 10, 27], "chang": 5, "check": [4, 5, 16, 18, 24], "check_random_st": 6, "chevali": [2, 5, 6, 14, 17, 18, 20, 27], "choic": [2, 5], "choos": 5, "chunk": 5, "citat": 27, "class": [9, 10, 11, 20], "classif": [1, 5, 8, 12, 20, 28], "clip": 4, "clone": [4, 7, 9, 27], "close": [2, 5, 14, 17, 19, 23, 26], "closer": 2, "cludl": [2, 5], "cluster": [2, 14, 17, 19, 20, 27], "clustered_infer": [2, 5], "cm": 4, "cmap": 7, "code": [1, 2, 3, 4, 5, 6, 7, 16, 18, 24], "coef0": 7, "coeffici": [3, 6], "color": [3, 4, 6, 7], "colormap": 4, "column": [4, 16], "com": [6, 27], "combin": [5, 7], "command": 27, "compar": [2, 3, 4, 5], "comparison": [5, 12], "compat": [9, 10, 11], "compress": [2, 5, 14, 17], "comput": [5, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 23, 26, 27], "compute_pv": 4, "concat": 4, "concept": 2, "concern": 2, "concurr": 5, "condit": [1, 4, 5, 7, 8, 9, 10, 27, 28], "condition_mask": 5, "confer": [4, 5, 6, 7, 9, 10, 12, 18, 20, 27], "confid": [5, 16, 27], "connect": [2, 5], "consecut": 18, "conserv": [2, 5], "consid": [2, 5, 7, 13, 16, 17, 18], "consider": [7, 16], "consist": [2, 5], "constant": 18, "constrain": 6, "construct": [2, 20, 21], "construct_method": 20, "contain": [2, 4, 5, 16, 23, 25], "context": [7, 27], "continu": [16, 18, 24], "contrarili": 7, "contrast": 5, "contribut": 27, "control": [2, 4, 5, 6, 7, 14, 17, 18, 20, 21, 24, 27], "converg": 5, "convergencewarn": 5, "coolwarm": 7, "corner": 2, "corr_mat": 7, "correct": [2, 5, 14, 17, 19, 23], "correction_clust": [2, 5], "correction_no_clust": 2, "correl": [2, 3, 4, 5, 6, 7, 18, 20, 21, 22], "correspond": [2, 5, 7, 20], "cortex": 5, "costli": 4, "cov_estim": [20, 21], "cov_hat": 18, "covari": [9, 10, 18, 20, 21], "covariate_estim": 4, "cpi": 7, "cpi_importance_list": 4, "cpi_linear": 7, "cpi_non_linear": 7, "cpi_pval": 4, "cpi_vim_arr": 4, "cpu": [14, 16, 17, 18, 19, 23, 24, 25], "creat": [2, 4, 5], "cross": [4, 7, 18, 23, 24, 25], "cumul": 23, "curran": [4, 7, 9, 10], "current": [2, 14, 16, 17, 19], "cut_coord": 5, "cutoff": 12, "cv": [5, 7], "d": [2, 7, 27], "d0crt": 3, "d60e14c19cd6e0fc38556ad29ac8fbc9": [4, 7, 9, 10], "daniel": 20, "data": [1, 4, 8, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28], "data_simul": 6, "datafram": [4, 5], "dataset": [1, 2, 8, 27, 28], "daum\u00e9": [6, 20], "davatziko": [5, 12], "dcrt": [1, 8, 28], "dcrt_zero": 3, "de": [2, 16, 27], "deal": 2, "decemb": 21, "decision_funct": [7, 9, 10, 11], "decod": [5, 27], "def": [2, 4, 5, 6], "def37a305edfda829916fa14c9ea08f8": 5, "default": [5, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 23, 24, 25, 26], "defin": [2, 20], "degre": [4, 7, 16], "delta": 2, "demonstr": 4, "deni": [4, 7, 9, 10], "depend": [2, 4, 5, 20], "deprec": 4, "derandom": 6, "derandomis": 6, "deriv": [2, 5, 12], "describ": [2, 6, 10], "design": [2, 16, 21, 22], "desir": [6, 20, 21], "desparsifi": [2, 5, 14, 16, 17, 18, 19, 27], "desparsified_lasso": 2, "destroi": 4, "detail": [2, 27], "determin": 23, "develop": 27, "deviat": [2, 7, 12, 18, 22, 24, 25], "dezeur": [16, 27], "df_plot": 4, "diabet": [1, 8, 28], "diamet": 2, "diamond": 7, "did": 5, "diff": 7, "differ": [2, 5, 7, 9, 27], "dim": 5, "dimens": 2, "dimension": [2, 4, 5, 6, 9, 13, 14, 16, 17, 19, 20, 21], "directli": [4, 18], "directori": [14, 16, 17, 19, 20], "discimin": 5, "discov": 5, "discoveri": [2, 5, 6, 7, 20, 21, 27], "discrimin": 5, "displai": 5, "distanc": 2, "distil": [1, 8, 28], "distrib": 26, "distribut": [5, 6, 7, 23, 26], "divid": [2, 5], "do": [2, 5, 20, 21], "doc": 27, "doe": [2, 4, 5], "dof_ajdust": 16, "doi": [4, 6, 7, 9, 20, 27], "done": [5, 14, 16, 17, 19, 20], "download": [1, 2, 3, 4, 5, 6, 7, 27], "dramat": 2, "draw": 2, "drawback": 6, "drop": 4, "dual": [16, 18, 24], "dualiti": 5, "due": [2, 5], "dure": [14, 16, 18, 19, 23, 24, 25], "e": [2, 4, 5, 6, 20, 23, 25, 27], "each": [9, 16, 18, 27], "eas": [2, 4], "ebh": 20, "ecdl": 27, "edg": 2, "editor": [4, 6, 7, 9, 10, 20], "eeg": [18, 27], "effect": [14, 17, 19, 23, 26], "either": 21, "elaps": 5, "els": [2, 5, 6], "emmanuel": [6, 21], "empir": [6, 20, 21], "empti": 5, "enabl": 2, "encludl": [2, 5], "end": [2, 3, 4, 5, 6, 7], "enet_coordinate_descent_gram": 5, "enfold": 2, "engemann": [4, 7, 9, 10, 27], "ensembl": [2, 5, 17, 27], "ensemble_clustered_infer": [2, 5], "ensembling_method": 17, "ensur": 16, "enumer": [4, 7], "ep": [18, 24], "epsilon": [2, 7], "equal": [2, 16, 23], "equi": [20, 21], "equival": [20, 21], "error": [2, 3, 24], "estim": [3, 4, 5, 6, 7, 9, 10, 11, 12, 14, 16, 17, 18, 19, 20, 21, 24, 25, 26], "et": [2, 4, 5, 6, 7, 9, 10, 12, 20, 21], "euclid": 27, "eval": 20, "eval_select": 6, "evalu": [9, 10, 11], "everi": [2, 14, 17, 18], "exampl": [2, 3, 4, 5, 6, 7, 8, 28], "exclus": 4, "execut": [8, 28], "executor": 7, "exemplifi": 7, "exhibit": [2, 6], "exp": 7, "expect": 5, "experi": 2, "express": 7, "extern": 7, "extract": 5, "f": [2, 3, 4, 5, 6, 7, 27], "face": 5, "fail": 7, "fake": 4, "fals": [2, 3, 5, 6, 7, 16, 20, 21, 27], "fan": [6, 21, 27], "fdp": 6, "fdp_eval": 6, "fdp_mx": 6, "fdp_pval": 6, "fdps_eval": 6, "fdps_mx": 6, "fdps_pval": 6, "fdr": [6, 20, 21], "fdr_control": 20, "feasibl": 2, "featur": [2, 5, 7, 22], "feature_extract": [2, 5], "feature_nam": 4, "featureagglomer": [2, 14, 17], "fetch_haxbi": 5, "fig": [2, 3, 4, 7], "figsiz": [2, 3, 6, 7], "figur": 6, "file": [4, 5, 7, 8, 9, 10, 28], "filter": 2, "final": [2, 5, 7], "finish": 5, "first": [2, 5, 7, 17], "fit": 7, "fit_i": 18, "fit_transform": 5, "fix": [4, 20], "fixedloc": 4, "flatten": 2, "flier": 7, "float": [12, 13, 14, 16, 17, 18, 20, 21, 22, 23, 24], "fmri": [1, 8, 27, 28], "fmri_filenam": 5, "fmri_mask": 5, "focu": 5, "fold": [4, 7], "follow": [2, 4, 27], "font": [3, 6], "forest": [1, 4, 7, 8, 28], "formal": 2, "formul": 5, "formula": [7, 13, 17], "four": 2, "foygel": 6, "fr": 5, "frac": 7, "fraction": [14, 17], "freedom": 16, "frequenc": [16, 20, 23], "friedman": 24, "from": [2, 3, 5, 6, 7, 8, 16, 26, 27, 28], "full": [2, 3, 4, 5, 6, 7], "func": 5, "function": [3, 7, 9, 10, 11, 13, 14, 15, 17, 19, 20, 23, 27], "fwer": [2, 5], "fwer_target": 2, "g": [2, 5, 27], "galleri": [2, 3, 4, 5, 6, 7, 28], "gamma": [6, 13, 17, 20], "gamma_min": [13, 17, 20], "gaonkar": [5, 12], "gap": [5, 16, 18, 24], "gaussian": [2, 5, 7, 16, 21, 22], "geer": [2, 16, 27], "gener": [1, 3, 4, 5, 6, 14, 16, 17, 20, 21, 22], "get": 3, "get_cmap": 4, "get_fdata": 5, "get_legend_handles_label": 7, "get_xaxi": 2, "get_yaxi": 2, "git": 27, "github": [2, 27], "give": 18, "given": [4, 7, 14, 16, 17, 18, 19, 20], "globerson": [4, 7, 9, 10], "go": [2, 3, 4, 5, 6, 7], "gold": [6, 21, 27], "good": 5, "gramfort": [18, 27], "greater": 2, "green": 7, "grei": 7, "grid": [23, 25], "grid_to_graph": [2, 5], "ground": [5, 7], "ground_truth_legend": 7, "group": [2, 4, 5, 9, 12, 14, 17, 18, 19, 27], "guarante": [2, 5], "gz": 5, "h": [2, 16, 27], "ha": [2, 4, 5, 6, 16], "hal": [6, 20], "handl": [7, 27], "hard": 5, "hardt": [4, 7, 9, 10], "have": [2, 5, 18, 27], "haxbi": 27, "haxby2001": 5, "haxby_dataset": 5, "header": 5, "heidelberg": [5, 12], "height": 7, "here": [5, 7, 27], "hidimstat": [2, 3, 4, 5, 6, 7], "hierarch": [14, 17], "high": [2, 4, 5, 6, 9, 13, 14, 16, 17, 19, 20, 21], "higher": 2, "highli": 4, "highlight": 7, "histgradientboostingregressor": 4, "hline": 6, "hochberg": 20, "hold": 2, "home": [4, 5], "hostedtoolcach": [5, 7], "hous": 5, "how": [7, 27], "howev": [2, 4, 5], "html": [6, 20, 27], "http": [2, 4, 5, 6, 7, 9, 10, 20, 27], "hyper": [2, 23, 25], "hypothesi": [16, 27], "i": [2, 3, 4, 5, 6, 7, 9, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26, 27], "idea": 2, "ideal": 27, "identifi": 7, "ie": [14, 17, 19, 23, 26], "iii": [6, 20], "iinfo": 6, "illustr": [2, 7, 27], "im": [2, 5], "imag": [2, 5, 12, 18, 27], "img": 5, "imp_cpi_linear": 7, "imp_cpi_non_linear": 7, "imp_pi_non_linear": 7, "impact": 4, "implement": [3, 9, 10, 11, 20], "import": [1, 8, 9, 10, 11, 27, 28], "importance_arr": 7, "importance_linear": 7, "importance_list": 7, "importance_non_linear": 7, "important_legend": 7, "important_pi": 7, "imputation_model": [4, 7, 9], "imshow": [2, 5], "inc": [4, 7, 9, 10], "includ": [5, 20], "increas": [5, 16, 20, 23], "inde": 2, "index": [7, 9, 20, 21], "infer": [6, 12, 14, 17, 19, 20, 21], "inference_method": 17, "infernec": 2, "influenc": 4, "inform": [4, 7, 9, 10, 18, 27], "input": [4, 20], "input_data": 5, "inria": [2, 27], "inspir": 7, "instanc": 7, "instead": 4, "int": [9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], "int32": 6, "integr": 4, "intellig": [9, 27], "intercept": 16, "interest": [4, 7, 16], "intern": [5, 6, 12, 20, 27], "interv": [16, 27], "intervent": [5, 12, 27], "introduc": [2, 4, 5, 6, 20], "introduct": 5, "intuit": 7, "invers": [5, 23], "inverse_transform": 5, "io": [2, 27], "ipynb": [2, 3, 4, 5, 6, 7], "isol": 5, "item": 7, "iter": [5, 16, 18, 20, 24], "its": [4, 5, 7], "j": [2, 5, 7, 14, 17, 18, 24, 27], "janson": [6, 21, 27], "jasa": 20, "javanmard": [2, 16, 27], "jerom": [6, 20], "jinchi": [6, 21], "job": [7, 9, 10, 11], "joblib": [7, 14, 16, 19, 20, 27], "joblib_verbos": 20, "joblib_versob": 20, "journal": [6, 13, 16, 20, 27], "jrsssb": 6, "jul": [6, 20], "juli": 4, "jupyt": [1, 2, 3, 4, 5, 6, 7], "k": [2, 4, 7, 9, 10], "kei": 3, "kernel": 7, "kf": 4, "kfold": [4, 18, 24], "kind": 27, "kneib": 4, "knockoff": [1, 8, 20, 21, 27, 28], "knockoff_aggreg": 6, "kwarg": [5, 14, 17, 19], "l": [4, 7, 13, 27], "label": [4, 5, 6, 7, 14, 17, 20], "labelbottom": 2, "labelleft": 2, "lack": [2, 7], "largest": 2, "largest_singular_valu": 12, "lasso": [1, 2, 5, 8, 14, 16, 17, 18, 19, 24, 27, 28], "lasso_cv": [20, 21], "lassocv": [18, 24], "lastli": 2, "latest": 27, "laur": 4, "layout": 6, "lead": 2, "leak": 7, "learn": [4, 6, 7, 9, 10, 11, 14, 16, 17, 20, 27], "learner": [1, 8, 28], "leav": 10, "ledoit_wolf": [20, 21], "ledoitwolf": 20, "left": [2, 7], "legend": [4, 6, 7], "len": 6, "length": [9, 18, 24], "leo": [4, 7], "less": 5, "let": 5, "level": [2, 4, 6, 9, 14, 16, 17, 19, 20, 21, 22, 23], "leverag": [2, 6], "levin": [4, 7, 9, 10], "lib": [5, 7], "like": 20, "limit": [2, 4], "linalg": 7, "line": [5, 7], "line2d": 7, "linear": [2, 3, 7, 14, 16, 17, 23, 25, 27], "linear_model": [4, 5, 7], "linestyl": 7, "linewidth": 3, "linkag": 2, "linspac": 7, "list": [9, 13, 20, 23, 25], "list_one_sided_pv": 13, "littl": 2, "load": 5, "load_diabet": 4, "loc": [6, 7], "local": 27, "loco_importance_list": 4, "loco_pv": 4, "loco_vim_arr": 4, "log10": 4, "log_": 4, "log_loss": 7, "logical_or": [2, 5], "logspac": [4, 7, 23, 25], "loki": 7, "lokybackend": 5, "look": 5, "loss": [4, 7, 9, 10, 11], "low": [16, 27], "lower": [2, 7, 16], "lowest": [13, 17], "luca": [6, 21], "luka": 20, "lv": [6, 21, 27], "lw": 7, "m": [4, 7, 9, 10, 16], "machin": [4, 6, 7, 16, 20, 27], "made": 4, "magnitud": 18, "mai": [5, 16], "make": [2, 7, 14, 16, 17, 19, 27], "mani": 5, "map": [2, 5, 12, 27], "mar": 9, "margin": 5, "marker": 7, "markers": 7, "mask": 5, "mask_img": 5, "mask_img_": 5, "masker": 5, "mass": 7, "match": 9, "math": 21, "matplotlib": [2, 3, 4, 6, 7, 27], "matplotlibdeprecationwarn": 4, "matrix": [2, 7, 14, 16, 17, 18, 19, 20, 21, 22], "matshow": 7, "max": 6, "max_it": [16, 18, 24], "maximum": [3, 16, 18, 24], "mb": [2, 3, 4, 5, 6, 7, 8, 28], "md": 5, "md5sum": 5, "mean": [4, 5, 7, 18, 24, 26], "mean_img": 5, "mean_vim": 4, "measur": [1, 8, 16, 20, 28], "median": [7, 17, 18], "medic": [5, 12, 27], "meg": [18, 27], "meier": [13, 20], "meinshausen": [13, 20], "mem": [8, 28], "memori": [2, 3, 4, 5, 6, 7, 14, 16, 17, 19, 20, 21], "messag": [14, 16, 17, 19, 20, 23], "method": [2, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 27], "methodologi": [6, 16, 27], "metric": [3, 4, 7], "might": 5, "mimic": 7, "min": 5, "mind": [2, 27], "minimum": 20, "minu": [14, 17, 19, 23, 26], "minut": [2, 3, 4, 5, 6, 7], "mline": 7, "mlr": [6, 20], "model": [2, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 21, 27], "model_linear": 7, "model_linear_c": 7, "model_non_linear": 7, "model_non_linear_c": 7, "model_select": [4, 7], "model_x_knockoff": 6, "moment": 26, "montanari": [16, 27], "more": [2, 5, 7, 20], "mse": 4, "much": [2, 5], "multi": [18, 27], "multipl": [2, 5, 6, 14, 17, 19, 20, 23, 27], "multitasklassocv": 18, "multivari": 7, "multivariate_1d_simul": 3, "multivariate_norm": 7, "multivariate_simul": 2, "must": [9, 10, 11, 18], "mx": 6, "mx_select": 6, "n": [3, 6, 13], "n_bootstrap": [5, 6, 17, 20], "n_cluster": [2, 5, 6, 14, 17], "n_featur": [2, 3, 5, 7, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], "n_fold": 4, "n_iter": [7, 13], "n_job": [2, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25], "n_permut": [4, 5, 7, 9, 11, 23], "n_sampl": [2, 3, 5, 7, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], "n_signal": 3, "n_split": [4, 7], "n_subject": 6, "n_time": [14, 17, 18, 19], "n_x": [2, 5], "n_y": [2, 5], "n_z": 5, "name": 4, "naumann": [4, 7, 9, 10], "nb": 6, "ncol": 3, "ndarrai": [12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26], "nearbi": 2, "neccessari": 27, "necessari": 2, "need": 27, "neg": [14, 17, 19, 23, 26], "neighbor": [2, 5, 22], "neural": [4, 7, 9, 10, 18, 27], "neurip": [4, 7, 9, 10, 18, 27], "neuroimag": [5, 27], "new": [4, 27], "next": 5, "nguyen": [2, 5, 6, 14, 17, 20, 27], "nguyen20a": [6, 20], "nicolai": 20, "niftimask": 5, "nii": 5, "nilearn": 5, "nilearn_data": 5, "nitrc": 5, "nodewis": 16, "nois": [2, 3, 7, 16, 18, 22, 24], "noise_i": 7, "nomin": 3, "non": [3, 4, 6, 7, 14, 16, 17, 19, 20, 23], "non_zero_index": 6, "none": [2, 5, 6, 7, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26], "nonzero": 5, "norm": [4, 26], "normal": [6, 7, 26], "notabl": [2, 5, 6, 16], "note": [2, 16], "notebook": [1, 2, 3, 4, 5, 6, 7], "now": [2, 5, 27], "np": [2, 3, 4, 5, 6, 7, 23, 25], "nrow": 3, "nsubject": 6, "number": [2, 3, 4, 5, 6, 9, 10, 11, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25], "numer": [14, 17, 19, 23, 26], "numpi": [2, 3, 4, 5, 6, 7, 27], "nwith": 2, "object": [2, 7, 14, 16, 17, 18, 19, 20, 24], "observ": [3, 6], "obtain": [5, 7], "occur": 2, "octob": [4, 5, 7, 12], "off": 2, "offer": 5, "offset": [20, 21], "oh": [4, 7, 9, 10], "oj": 9, "one": [2, 4, 5, 7, 13, 14, 17, 19, 23, 26], "one_minus_pv": [2, 5, 14, 17, 19, 26], "one_minus_pval_ada_svr": 5, "one_minus_pval_cdl": 5, "one_minus_pval_corr": [2, 14, 17, 19, 23], "one_minus_pval_corr_ridge_perm_test": 5, "one_minus_pval_corr_svr_perm_test": 5, "one_minus_pval_ecdl": 5, "one_minus_pval_std_svr": 5, "one_sided_pv": 13, "ones": 4, "onli": [2, 4, 5, 16, 17, 26, 27], "opiton": 26, "oppos": 7, "opt": [5, 7], "optim": [2, 16, 18, 20, 21, 24, 27], "option": [12, 13, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26], "orang": 7, "order": 18, "org": [5, 6, 9, 27], "origin": [2, 5, 14, 16, 17], "orign": 5, "orlean": 27, "other": [5, 16], "otherwis": [9, 16, 18, 23], "oup": 6, "our": 27, "out": [5, 10], "outcom": [3, 4], "output": [5, 14, 16, 17, 19, 20], "over": [5, 6, 7], "p": [3, 5, 6, 13, 14, 16, 17, 19, 20, 23, 26, 27], "packag": [5, 7, 27], "pan": [6, 21, 27], "panda": [4, 5], "paper": [4, 7, 9, 10, 27], "paper_fil": [4, 7, 9, 10], "parallel": [5, 9, 10, 11, 14, 19, 20], "param_distribut": 7, "paramet": [5, 6, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27], "parametr": 5, "parcel": 5, "parralel": [16, 23], "partern": 5, "partit": [18, 24], "pass": [14, 17, 18, 19, 24], "patern": 5, "path": [14, 16, 17, 18, 19, 20, 24], "pattern": 5, "pd": [4, 5], "pdf": [4, 6, 7, 9, 10], "percentil": 20, "perform": [2, 3, 4, 9, 10, 11], "perm": 5, "permut": [5, 7, 9, 10, 11, 23, 27], "permutation_import": 4, "permutation_test": 5, "permutation_test_cv": 5, "permutationimport": [4, 7], "peter": 20, "php": [5, 9], "pi": [4, 7], "pi_importance_list": 4, "pi_non_linear": 7, "pi_pval": 4, "pi_vim_arr": 4, "pip": 27, "pleas": [2, 5], "plot": [6, 7], "plot_2d_simulation_exampl": [2, 8, 27, 28], "plot_dcrt_exampl": [3, 8, 28], "plot_diabetes_variable_importance_exampl": [4, 8, 28], "plot_fmri_data_exampl": [5, 8, 27, 28], "plot_knockoff_aggreg": [6, 8, 28], "plot_map": 5, "plot_meg_data_exampl": 27, "plot_result": 6, "plot_stat_map": 5, "plot_variable_importance_classif": [7, 8, 28], "plt": [2, 3, 4, 6, 7], "pmlr": [6, 20, 27], "poli": 7, "polynomi": 7, "popul": 7, "posit": [3, 7, 14, 17, 19, 23, 26], "possibl": 5, "potenti": 9, "power": [2, 3, 5, 6], "power_ev": 6, "power_mx": 6, "power_pv": 6, "powers_ev": 6, "powers_mx": 6, "powers_pv": 6, "pp": [5, 12, 27], "practic": 2, "precis": [2, 5], "precomput": 5, "predict": [2, 4, 5, 9, 10, 11], "predict_proba": [9, 10, 11], "preprint": [2, 14, 16, 17, 27], "preprocess_haxbi": 5, "prescal": 16, "present": [2, 5, 12], "preserv": 4, "press": [6, 20], "previou": 5, "previous": 5, "print": [3, 4, 14, 16, 17, 19, 20, 23], "problem": [2, 4, 5, 7, 16, 27], "procedur": [6, 12, 13, 18, 19, 20, 21, 24], "proceed": [4, 6, 7, 9, 10, 20, 27], "process": [2, 4, 6, 7, 9, 10, 18, 20, 27], "process_executor": 7, "produc": 5, "progress": [16, 20, 23], "project": 27, "projecteuclid": 27, "proport": 23, "provid": [2, 5, 9, 27], "pval": [2, 4, 5, 14, 17, 19, 20, 26], "pval_ada_svr": 5, "pval_arr": 7, "pval_cdl": 5, "pval_corr": [2, 14, 17, 19, 23], "pval_corr_ridge_perm_test": 5, "pval_corr_svr_perm_test": 5, "pval_ecdl": 5, "pval_from_cb": 2, "pval_from_scal": 5, "pval_std_svr": 5, "py": [2, 3, 4, 5, 6, 7, 8, 27, 28], "pymvpa": 5, "pyplot": [2, 3, 4, 6, 7], "pytest": 27, "python": [1, 2, 3, 4, 5, 6, 7], "python3": [5, 7], "qkad085": 6, "quantifi": 2, "quantil": [6, 7, 13, 17, 20], "quit": [2, 5], "r": [3, 4, 16, 24, 27], "r2_score": 4, "radiu": 2, "randint": 6, "randn": 7, "random": [1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 14, 17, 18, 20, 21, 24, 28], "random_st": [4, 6, 7, 9, 10, 11, 20], "randomforest": 3, "randomizedsearchcv": 7, "randomst": 7, "rang": [2, 3, 4, 6, 7, 16], "rate": [3, 6, 20, 21, 27], "rather": 5, "ratio": [3, 6], "ravel": 2, "rcond": 12, "rcparam": [3, 6], "read": 2, "read_csv": 5, "readabl": 5, "readm": 5, "real": 20, "realist": 5, "reason": [2, 5], "recommend": 2, "reconstruct": 4, "recov": [2, 5], "recoveri": [1, 8, 27, 28], "red": [4, 6], "reduc": [2, 5], "reduct": 2, "refer": [9, 10, 11, 12, 13, 14, 16, 17, 18, 20, 21, 24], "reflect": 4, "region": [2, 5, 16, 27], "regress": [2, 4, 13, 16, 18, 20, 24, 27], "regressor": 4, "regressor_list": 4, "regular": [5, 23, 25], "reid": 18, "relationship": [3, 4, 7], "relax": [2, 14, 17, 27], "relev": [2, 3, 5, 27], "relu": 3, "remain": [4, 5], "remov": 4, "ren": 6, "repetit": 3, "report": 20, "repres": 2, "request": 6, "requir": [2, 9, 27], "resampl": 5, "rescal": 7, "research": [6, 16, 20, 27], "reshap": [2, 20], "reshaping_funct": 20, "residu": [4, 16, 18], "residual_method": 16, "respons": 21, "result": 6, "results_forest": 3, "results_lasso": 3, "return": [2, 4, 5, 6, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], "rho": [3, 6, 22], "ridg": [4, 5], "ridgecv": [4, 7], "right": [6, 7], "rina": 6, "ritov": [16, 27], "rng": [6, 7], "roi_siz": 2, "roi_size_extend": 2, "root_mean_squared_error": [4, 9, 10, 11], "rotat": [6, 7], "rough": 2, "round": 2, "royal": [6, 16, 27], "rssb": 6, "run": [2, 3, 4, 5, 6, 7, 9, 10, 11, 23, 25, 27], "rune": [14, 17, 19], "runner": [4, 5], "saenko": [4, 7, 9, 10], "salmon": [2, 5, 14, 17, 18, 27], "same": [2, 17, 18], "sampl": [2, 4, 14, 17, 20, 22], "satisfi": 5, "scale": [5, 12, 16, 25], "scatter": [6, 7], "scenario": [2, 3], "scheme": [4, 20, 21], "scikit": [9, 10, 11, 14, 17, 27], "scipi": [4, 7, 27], "score": [4, 5, 7, 9, 10, 11, 20, 21, 23, 26], "screen": 3, "script": [7, 27], "sdp": [20, 21], "search": [23, 25], "second": [2, 3, 4, 5, 6, 7], "section": 2, "see": [2, 4, 5, 9], "seed": [2, 3, 5, 6, 7, 9, 10, 11, 14, 17, 18, 20, 21, 22, 23, 24], "seed_list": 6, "seem": [2, 5], "select": [2, 6, 20, 21, 27], "selected_cdl": 2, "selected_dl": 2, "selected_ecdl": 2, "self": 5, "sent": 20, "sep": 5, "seri": [6, 16, 27], "serv": [14, 17], "session": 5, "session_label": 5, "session_target": 5, "set": [2, 3, 4, 5, 9, 12, 23, 25, 27], "set_clim": 2, "set_tick": 4, "set_ticklabel": 4, "set_titl": [2, 3], "set_vis": 2, "set_xlabel": [4, 7], "set_xtick": 7, "set_xticklabel": [3, 4], "set_ylabel": [4, 7], "set_ylim": 3, "set_ytick": 7, "setp": 7, "sever": [17, 27], "sf": 4, "sform": 5, "shape": [2, 4, 5, 7, 12, 13, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26], "short": [5, 7], "shorter": 5, "shortli": 2, "should": [4, 5, 16], "show": [2, 3, 4, 5, 6], "shown": 5, "shrink": [20, 21], "shuffl": [4, 7, 22, 23], "side": [13, 26], "sigma": [2, 22], "sigma_hat": 24, "signal": 3, "signific": [4, 5, 12], "significantli": 2, "sim_ind": 3, "similarli": 2, "simpl": 18, "simpli": 7, "simu_data": 6, "simul": [1, 8, 27, 28], "sinc": [2, 5, 14, 16, 17], "singh": [6, 20], "singl": [4, 9, 27], "single_run": 6, "singular": 12, "sinica": 24, "site": [5, 7], "size": [2, 3, 6, 7, 22], "skip": 2, "sklearn": [2, 4, 5, 6, 7, 14, 17], "small": [2, 5, 12], "smaller": [2, 12, 16, 18, 24], "smooth": 2, "smooth_x": 2, "smoothing_fwhm": 5, "snr": 3, "so": 2, "societi": [6, 16, 27], "solut": [2, 4, 5, 17], "solv": 27, "some": [2, 5, 7], "sourc": [1, 2, 3, 4, 5, 6, 7, 18, 27], "space": [2, 4, 5], "spars": 20, "sparsifi": 27, "sparsiti": 6, "spatial": [2, 5, 14, 17, 27], "spatio": [18, 27], "specif": 7, "specifi": 7, "sphinx": [1, 2, 3, 4, 5, 6, 7], "sphinx_bootstrap_them": 27, "sphinx_galleri": 27, "split": [4, 7], "springer": [5, 12, 27], "spuriou": [5, 7], "squar": 2, "srt": 20, "stack": 7, "stand": 5, "standard": [2, 4, 5, 7, 12, 18, 20, 21, 22, 24, 25], "standardized_svr": 5, "star": 7, "stat": [4, 7, 20, 21, 23], "stat_tool": [2, 5], "stationari": 18, "statist": [2, 3, 4, 5, 6, 7, 9, 10, 12, 13, 14, 16, 17, 18, 19, 20, 21], "statistica": 24, "std": [4, 7], "std_vim": 4, "stdout": 20, "step": [5, 14, 18, 19], "still": 2, "stop": 7, "str": [9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 26], "stratifiedkfold": 7, "strength": 23, "string": [14, 16, 17, 19, 20], "strobl": 4, "structur": [2, 5, 7, 22, 27], "studi": 24, "sub": [2, 4], "subj2": 5, "subplot": [2, 3, 4, 7], "subsampl": [14, 17], "subset": 4, "substitut": 4, "suitabl": 5, "sum": [2, 3], "summari": 2, "support": [1, 7, 8, 9, 10, 11, 22, 27, 28], "support_s": [3, 22], "surviv": [5, 13, 23], "svc": 7, "svm": [5, 7, 12], "svr": [5, 23, 25], "svr_permutation_test_infer": 5, "sylvain": [6, 20], "sym": 6, "system": [4, 7, 9, 10, 18, 27], "t": [2, 4, 5, 7, 9, 10, 14, 17, 27], "tab": [4, 7], "tab10": 4, "tackl": 27, "take": [2, 5, 18], "tar": 5, "target": [2, 4, 5, 7, 12, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25], "target_fw": 5, "task": [5, 18, 27], "tck_id": 7, "techniqu": [2, 5], "tempor": [14, 17, 18, 19, 27], "term": 7, "termin": 27, "test": [1, 2, 5, 7, 8, 14, 16, 17, 19, 20, 21, 23, 27, 28], "test_index": 4, "test_scor": 21, "text": [4, 7], "than": [2, 5, 7, 12, 16, 18, 20, 24], "thank": [2, 5], "thei": [4, 5], "them": 2, "theoret": [2, 5], "therefor": [4, 7], "thi": [7, 14, 16, 17, 18, 20, 24, 27], "thin": 2, "third": 7, "thirion": [2, 4, 5, 6, 7, 9, 10, 14, 17, 18, 20, 27], "thoma": 4, "those": [2, 5], "thr_c": 2, "thr_nc": 2, "thre": 21, "three": 27, "thresh": 5, "threshold": [5, 7, 20, 21], "through": [4, 7, 9, 10, 27], "thu": [4, 5], "tibshirani": 24, "tick": 4, "tick_param": 2, "tight_layout": 2, "time": [2, 3, 4, 5, 6, 7, 17, 18], "timeout": 7, "titl": [2, 4, 5, 6], "tm08647": 20, "to_numpi": 5, "toeplitz": [7, 22], "tol": [16, 18, 24], "toler": [2, 5, 16, 18, 24], "too": [5, 7], "top": 2, "total": [2, 3, 4, 5, 6, 7, 8, 28], "toward": 4, "train": 7, "train_index": 4, "train_siz": [2, 14, 17], "transform": [9, 10, 11], "translat": [2, 5], "tresh": 5, "true": [2, 3, 4, 5, 6, 7, 16, 18, 20, 21, 22], "truli": 4, "truth": 7, "try": 5, "ttest_1samp": 7, "tuan": [6, 20], "two": [2, 4, 5, 6, 7, 14, 17, 18, 19], "type": [2, 3, 4, 5, 26], "typei_error": 3, "u": [5, 27], "uncertainti": 2, "uncompress": [5, 14, 17], "under": [4, 7, 20], "underli": 26, "unecessari": 16, "uniqu": [4, 5], "unlik": 2, "unstabl": 6, "until": [16, 18, 24], "up": 19, "updat": [3, 6, 16, 18, 24], "upper": [7, 16], "url": [4, 6, 7, 9, 10, 20], "us": [1, 2, 5, 6, 7, 8, 9, 10, 11, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 28], "usa": 27, "usag": [2, 3, 4, 5, 6, 7], "userwarn": [4, 5, 7], "util": [5, 6], "v": [1, 5, 8, 28], "v119": [6, 20], "v38i10": 9, "val": [23, 25], "valid": [4, 7, 9, 10, 18, 23, 24, 25, 27], "valu": [3, 5, 6, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 23, 25, 26], "van": [2, 16, 27], "vancouv": 27, "var": 4, "variabl": [1, 3, 6, 8, 9, 10, 20, 21, 27, 28], "varianc": 24, "variant": 4, "varoquaux": [5, 27], "vector": [2, 7, 12, 14, 16, 17, 19, 20, 21, 22, 24, 25], "verbos": [3, 14, 16, 17, 19, 20, 21, 23], "veri": 5, "version": [4, 20, 27], "vert": 7, "via": 27, "vienna": 27, "view": 9, "vim": 4, "visibl": 2, "visual": 5, "volum": [4, 6, 7, 9, 10, 20], "voxel": 5, "w": 2, "wa": [2, 4], "walker": 18, "want": [5, 27], "ward": [2, 5, 14, 17], "warn": [5, 7], "we": [2, 4, 5, 6, 7, 14, 17, 19, 27], "wei": 16, "weight": [2, 5, 7], "weight_map_2d_extend": 2, "well": 7, "were": 7, "when": [2, 4, 5, 16, 23], "where": [4, 5, 7], "whether": [20, 21], "which": [2, 4, 5, 7, 18, 24], "while": [4, 7], "whisker": 7, "white": [2, 22], "width": [4, 7], "without": 2, "work": [4, 5, 27], "worker": [5, 7, 20], "would": 27, "wrap": [5, 19], "www": 5, "x": [2, 3, 4, 5, 6, 7, 12, 16, 18, 19, 20, 21, 22, 23, 24, 25, 27], "x1": 7, "x10": 7, "x2": 7, "x4": 7, "x6": 7, "x64": [5, 7], "x8": 7, "x9": 7, "x_init": [2, 14, 17], "x_test": 4, "x_tild": 21, "x_train": 4, "xmax": 6, "xmin": 6, "xtick": 6, "y": [2, 3, 4, 5, 6, 7, 12, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27], "y_cont": 7, "y_pred": 4, "y_test": 4, "y_train": 4, "y_true": 4, "yekuti": 20, "yingi": [6, 21], "ylabel": 6, "yoav": 20, "you": [2, 5, 16, 27], "ytick": 7, "yule": 18, "z": [5, 26], "zeilei": 4, "zero": [2, 6, 7, 12, 14, 16, 17, 19, 20, 23, 26], "zhang": [2, 16, 27], "zhimei": 6, "zip": [1, 2, 3, 4, 5, 6, 7], "zorder": 7, "zscore": [2, 5, 26], "zscore_from_pv": [2, 5], "zscore_img": 5, "zscore_threshold": 5, "zscore_threshold_clust": 5, "zscore_threshold_corr": 5, "zscore_threshold_no_clust": 5}, "titles": ["API Documentation", "Examples Gallery", "Support recovery on simulated data (2D)", "Distilled Conditional Randomization Test (dCRT) using Lasso vs Random Forest learners", "Variable Importance on diabetes dataset", "Support recovery on fMRI data", "Knockoff aggregation on simulated data", "Measuring variable importance in classification", "Computation times", "hidimstat.CPI", "hidimstat.LOCO", "hidimstat.PermutationImportance", "hidimstat.ada_svr", "hidimstat.aggregate_quantiles", "hidimstat.clustered_inference", "hidimstat.data_simulation", "hidimstat.desparsified_lasso", "hidimstat.ensemble_clustered_inference", "hidimstat.group_reid", "hidimstat.hd_inference", "hidimstat.knockoff_aggregation", "hidimstat.model_x_knockoff", "hidimstat.multivariate_1D_simulation", "hidimstat.permutation_test_cv", "hidimstat.reid", "hidimstat.standardized_svr", "hidimstat.zscore_from_pval", "HiDimStat: High-dimensional statistical inference tool for Python", "Computation times"], "titleterms": {"2d": 2, "ada_svr": 12, "aggreg": 6, "aggregate_quantil": 13, "algorithm": [2, 5], "analysi": [2, 5], "analyz": 4, "api": [0, 27], "baselien": 4, "baselin": 4, "build": 27, "choos": 2, "class": 0, "classif": 7, "cluster": 5, "clustered_infer": 14, "comparison": 3, "comput": [2, 3, 4, 7, 8, 28], "condit": 3, "cpi": [4, 9], "data": [2, 5, 6, 7], "data_simul": 15, "dataset": [4, 5], "dcrt": 3, "defin": 4, "depend": 27, "desparsified_lasso": 16, "diabet": 4, "dimension": 27, "distil": 3, "document": [0, 27], "ensemble_clustered_infer": 17, "estim": [0, 2], "exampl": [1, 27], "featureagglomer": 5, "fetch": 5, "fit": 4, "fmri": 5, "forest": 3, "from": 4, "function": [0, 2, 4, 5], "galleri": 1, "gather": 5, "gener": [2, 7], "given": 5, "group_reid": 18, "haxbi": 5, "hd_infer": 19, "hidimstat": [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27], "high": 27, "import": [2, 3, 4, 5, 6, 7], "infer": [2, 5, 7, 27], "initi": 5, "instal": 27, "knockoff": 6, "knockoff_aggreg": 20, "lasso": 3, "learner": 3, "load": 4, "loco": [4, 10], "main": 27, "make": 5, "measur": [4, 7], "method": 4, "model": 4, "model_x_knockoff": 21, "multivariate_1d_simul": 22, "need": [2, 3, 4, 5, 6, 7], "object": 5, "other": 27, "p": [4, 7], "paramet": 2, "perform": 5, "permut": 4, "permutation_test_cv": 23, "permutationimport": 11, "plot": [2, 3, 5], "preprocess": 5, "process": 3, "python": 27, "random": 3, "recoveri": [2, 5], "refer": [2, 4, 5, 6, 7, 27], "reid": 24, "result": [2, 4, 5], "score": 2, "script": [2, 3, 4, 5, 6], "sever": [2, 5], "simul": [2, 6], "specif": 2, "standardized_svr": 25, "statist": 27, "subject": 5, "support": [2, 5], "test": 3, "thi": [2, 3, 4, 5, 6], "threshold": 2, "time": [8, 28], "tool": 27, "us": [3, 4, 27], "v": 3, "valu": [4, 7], "variabl": [4, 7], "visual": 7, "z": 2, "zscore_from_pv": 26}})
\ No newline at end of file
diff --git a/docs/sg_execution_times.html b/docs/sg_execution_times.html
index 7a0e4d9..de69a60 100644
--- a/docs/sg_execution_times.html
+++ b/docs/sg_execution_times.html
@@ -110,7 +110,7 @@
       
   <section id="computation-times">
 <span id="sphx-glr-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">¶</a></h1>
-<p><strong>10:04.378</strong> total execution time for 6 files <strong>from all galleries</strong>:</p>
+<p><strong>09:52.927</strong> total execution time for 6 files <strong>from all galleries</strong>:</p>
 <div class="docutils container">
 <style scoped>
 <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -132,28 +132,28 @@
 </thead>
 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_knockoff_aggregation.html#sphx-glr-auto-examples-plot-knockoff-aggregation-py"><span class="std std-ref">Knockoff aggregation on simulated data</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_knockoff_aggregation.py</span></code>)</p></td>
-<td><p>05:31.198</p></td>
-<td><p>782.5</p></td>
+<td><p>05:27.443</p></td>
+<td><p>769.2</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_fmri_data_example.html#sphx-glr-auto-examples-plot-fmri-data-example-py"><span class="std std-ref">Support recovery on fMRI data</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_fmri_data_example.py</span></code>)</p></td>
-<td><p>01:29.290</p></td>
-<td><p>3331.0</p></td>
+<td><p>01:25.117</p></td>
+<td><p>3348.8</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_2D_simulation_example.html#sphx-glr-auto-examples-plot-2d-simulation-example-py"><span class="std std-ref">Support recovery on simulated data (2D)</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_2D_simulation_example.py</span></code>)</p></td>
-<td><p>01:09.382</p></td>
+<td><p>01:07.044</p></td>
 <td><p>704.9</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_dcrt_example.html#sphx-glr-auto-examples-plot-dcrt-example-py"><span class="std std-ref">Distilled Conditional Randomization Test (dCRT) using Lasso vs Random Forest learners</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_dcrt_example.py</span></code>)</p></td>
-<td><p>01:01.772</p></td>
-<td><p>642.6</p></td>
+<td><p>01:01.764</p></td>
+<td><p>643.1</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_variable_importance_classif.html#sphx-glr-auto-examples-plot-variable-importance-classif-py"><span class="std std-ref">Measuring variable importance in classification</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_variable_importance_classif.py</span></code>)</p></td>
-<td><p>00:44.372</p></td>
-<td><p>622.2</p></td>
+<td><p>00:43.289</p></td>
+<td><p>621.8</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_diabetes_variable_importance_example.html#sphx-glr-auto-examples-plot-diabetes-variable-importance-example-py"><span class="std std-ref">Variable Importance on diabetes dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_diabetes_variable_importance_example.py</span></code>)</p></td>
-<td><p>00:08.364</p></td>
-<td><p>626.5</p></td>
+<td><p>00:08.271</p></td>
+<td><p>626.2</p></td>
 </tr>
 </tbody>
 </table>