docs, MetidaBase 0.3

Project.toml

@@ -24,7 +24,7 @@ LineSearches = "7"
 Optim = "1"
 StatsBase = "0.29, 0.30, 0.31, 0.32, 0.33"
 julia = "1"
-MetidaBase = "0.2.2"
+MetidaBase = "0.3"
 #LoopVectorization = "0.12"
 
 [extras]

docs/src/details.md

@@ -28,11 +28,31 @@ V_{i} = Z_{i}GZ_i'+R_{i}
 #### REML
 
 ```math
-logREML(\theta,\beta) = -\frac{N-p}{2} - \frac{1}{2}\sum_{i=1}^nlog|V_{i}|-
+logREML(\theta,\beta) = -\frac{N-p}{2} - \frac{1}{2}\sum_{i=1}^nlog|V_{\theta, i}|-
 
--\frac{1}{2}log|\sum_{i=1}^nX_i'V_i^{-1}X_i|-\frac{1}{2}\sum_{i=1}^n(y_i - X_{i}\beta)'V_i^{-1}(y_i - X_{i}\beta)
+-\frac{1}{2}log|\sum_{i=1}^nX_i'V_{\theta, i}^{-1}X_i|-\frac{1}{2}\sum_{i=1}^n(y_i - X_{i}\beta)'V_{\theta, i}^{-1}(y_i - X_{i}\beta)
 ```
 
+Actually ``\mathcal{L}(\theta) = -2logREML`` used for optimization,  ``-2logREML = L_1(\theta) + L_2(\theta) + \L_3(\theta) + c``, where:
+
+```math
+L_1(\theta) = \frac{1}{2}\sum_{i=1}^nlog|V_{i}| \\
+
+L_2(\theta) = \frac{1}{2}log|\sum_{i=1}^nX_i'V_i^{-1}X_i| \\
+
+L_3(\theta) = \frac{1}{2}\sum_{i=1}^n(y_i - X_{i}\beta)'V_i^{-1}(y_i - X_{i}\beta)
+```
+
+ ```math
+  \nabla\mathcal{L}(\theta) = \nabla L_1(\theta) + \nabla L_2(\theta) + \nabla L_3(\theta)
+ ```
+
+```math
+\mathcal{H}\mathcal{L}(\theta) =  \mathcal{H}L_1(\theta)  + \mathcal{H}L_2(\theta) +  \mathcal{H} L_3(\theta)
+```
+
+
+
 #### Beta (β)
 
 ```math

src/Metida.jl

@@ -6,7 +6,7 @@ module Metida
 
 using Distributions, LinearAlgebra, StatsBase, ForwardDiff, CategoricalArrays#, LoopVectorization
 using Optim, LineSearches, MetidaBase
-#using StatsModels
+using StatsModels
 import MetidaBase: Tables, MetidaModel, AbstractCovarianceStructure, AbstractCovmatMethod, AbstractCovarianceType, AbstractLMMDataBlocks, MetidaTable, metida_table, PrettyTables
 
 import LinearAlgebra:checksquare