diff --git a/.github/workflows/R-CMD-check-macos.yaml b/.github/workflows/R-CMD-check-macos.yaml index 6404e91..8ff416b 100644 --- a/.github/workflows/R-CMD-check-macos.yaml +++ b/.github/workflows/R-CMD-check-macos.yaml @@ -39,26 +39,12 @@ jobs: steps: - uses: actions/checkout@v2 - - uses: r-lib/actions/setup-r@v1 - with: - r-version: ${{ matrix.config.r }} + - uses: r-lib/actions/setup-pandoc@v2 - - uses: r-lib/actions/setup-pandoc@v1 - - - name: Query dependencies - run: | - install.packages('remotes') - saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2) - writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version") - shell: Rscript {0} - - - name: Cache R packages - if: runner.os != 'Windows' - uses: actions/cache@v2 + - uses: r-lib/actions/setup-r@v2 with: - path: ${{ env.R_LIBS_USER }} - key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }} - restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1- + r-version: ${{ matrix.config.r }} + use-public-rspm: true - name: Install system dependencies run: | @@ -66,13 +52,22 @@ jobs: brew install mpfr brew install automake + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + cache-version: 1 + extra-packages: | + any::rcmdcheck + any::covr + any::remotes + gurobi=?ignore + needs: | + check + coverage + - name: Install dependencies run: | - options("install.packages.compile.from.source" = "never") - remotes::install_deps(dependencies = TRUE) - remotes::install_cran("rcmdcheck") - remotes::install_cran("covr") options("install.packages.compile.from.source" = "yes") + remotes::install_cran("sf") remotes::install_cran("RcppAlgos") shell: Rscript {0} @@ -83,19 +78,11 @@ jobs: sessioninfo::session_info(pkgs, include_base = TRUE) shell: Rscript {0} - - name: Check - run: | - rcmdcheck::rcmdcheck(args = c("--no-manual", "--as-cran", "--no-build-vignettes"), error_on = "warning", check_dir = "check") - shell: Rscript {0} + - uses: r-lib/actions/check-r-package@v2 + with: + upload-snapshots: true - name: Show testthat output if: always() run: find check -name 'testthat.Rout*' -exec cat '{}' \; || true shell: bash - - - name: Upload check results - if: failure() - uses: actions/upload-artifact@main - with: - name: ${{ runner.os }}-r${{ matrix.config.r }}-results - path: check diff --git a/DESCRIPTION b/DESCRIPTION index 4c1ab2b..16f87c7 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: surveyvoi Type: Package -Version: 1.0.5.1 +Version: 1.0.6 Title: Survey Value of Information Description: Decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving @@ -74,7 +74,6 @@ License: GPL-3 LazyData: true Language: en-US SystemRequirements: - C++11, JAGS (>= 4.3.0) (optional), fftw3 (>= 3.3), gmp (>= 6.2.1), @@ -85,7 +84,7 @@ SystemRequirements: URL: https://prioritizr.github.io/surveyvoi/ BugReports: https://github.com/prioritizr/surveyvoi/issues VignetteBuilder: knitr -RoxygenNote: 7.2.3 +RoxygenNote: 7.3.1 Encoding: UTF-8 Biarch: true Collate: diff --git a/NEWS.md b/NEWS.md index 6be89d5..a5bc177 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,9 @@ +# surveyvoi 1.0.6 + +- Fix installation for Windows on arm64 (#50). +- Fix aliasing for package overview help file (#49). +- Remove CXX specification in Makevars to avoid NOTEs in package checks. + # surveyvoi 1.0.5.1 - Update citation. diff --git a/R/env_div_survey_scheme.R b/R/env_div_survey_scheme.R index fa8a53c..2395036 100644 --- a/R/env_div_survey_scheme.R +++ b/R/env_div_survey_scheme.R @@ -69,7 +69,7 @@ NULL #' install the [Gurobi optimization software](https://www.gurobi.com/) and the #' \pkg{gurobi} R package because it can generate survey schemes much faster. #' Note that special academic licenses are available at no cost. -#' Installation instructions are available online for [Linux](https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html), [Windows](https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html), and [Mac OS](https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html) operating systems. +#' Installation instructions are [available online for Linux, Windows, and Mac OS operating systems](https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer). #' #' @references #' Faith DP & Walker PA (1996) Environmental diversity: on the best-possible diff --git a/R/feasible_survey_schemes.R b/R/feasible_survey_schemes.R index de68697..f9441cd 100644 --- a/R/feasible_survey_schemes.R +++ b/R/feasible_survey_schemes.R @@ -23,7 +23,8 @@ NULL #' Please note that this function requires the Gurobi optimization software #' () and the \pkg{gurobi} R package if different #' sites have different survey costs. Installation instruction are available -#' online for for [Linux](https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html), [Windows](https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html), and [Mac OS](https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html). +#' online for Linux, Windows, and Mac OS +#' (see ). #' #' @examples #' \dontrun{ diff --git a/R/package.R b/R/package.R index 2715bb1..919dd00 100644 --- a/R/package.R +++ b/R/package.R @@ -27,8 +27,8 @@ NULL #' @details #' Please note that several functions depend on #' the 'Gurobi' optimization software (available from ) -#' and the \pkg{gurobi} R package (installation instructions available for -#' [Linux](https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html), [Windows](https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html), and [Mac OS](https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html)). +#' and the \pkg{gurobi} R package (installation instructions +#' [available online for Linux, Windows, and Mac OS](https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer)). #' Additionally, the JAGS software #' (available from ) is required to fit #' hierarchical generalized linear models. @@ -38,8 +38,16 @@ NULL #' (accessible using the code `vignettes("surveyvoi")`). #' #' @name surveyvoi -#' @docType package -NULL +#' +#' @aliases surveyvoi-package +#' +#' @author +#' Package authors: +#' * Jeffrey O. Hanson \email{jeffrey.hanson@uqconnect.edu.au} [ORCID](https://orcid.org/0000-0002-4716-6134) +#' * Iadine Chadès \email{iadine.chades@csiro.au} [ORCID](https://orcid.org/0000-0002-7442-2850) +#' * Emma J. Hudgins \email{emma.hudgins@mail.mcgill.ca} [ORCID](https://orcid.org/0000-0002-8402-5111) +#' * Joseph R. Bennett \email{joseph.bennett@carleton.ca} [ORCID](https://orcid.org/0000-0002-3901-9513) +"_PACKAGE" # ensure package checks pass #' @importFrom utils zip diff --git a/cran-comments.md b/cran-comments.md index 411843a..8bc25b7 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,6 +1,6 @@ Dear CRAN volunteers, -Thank you very much for reviewing this submission. This submission aims to fix the issues causing the package to fail CRAN checks. Specifically, it fixes the compiler warnings (e.g., on Debian-clang flavor) and unit test errors (i.e., on Fedora flavors). I have also taken this opportunity to update the package to be compatible with the upcoming Matrix package (version >= 1.4-2), whilst maintaining backwards compatibility with previous versions. +Thank you for reviewing this submission. This submission contains updates for the _surveyvoi_ package to fix (i) aliasing for the package manual entry, (ii) uneeded C++11 specification, and (iii) installation for Windows on arm64 systems. Cheers, @@ -19,7 +19,7 @@ Jeff # R CMD check results -0 errors | 0 warnings | 2 notes +0 errors | 0 warnings | 3 notes # Notes @@ -35,59 +35,21 @@ Jeff **The package uses the gurobi R package that is distributed with Gurobi software suite (and not available on CRAN). The DESCRIPTION, README, and package documentation provide instructions for installing the gurobi R package.** -* Found the following (possibly) invalid URLs: - URL: https://doi.org/10.1111/1365-2664.14309 - From: README.md - Status: 503 - Message: Service Unavailable +* found the following (possibly) invalid URLs: + URL: https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer + From: man/approx_optimal_survey_scheme.Rd + man/env_div_survey_scheme.Rd + man/feasible_survey_schemes.Rd + man/geo_cov_survey_scheme.Rd + man/optimal_survey_scheme.Rd + man/surveyvoi.Rd + man/weighted_survey_scheme.Rd + inst/doc/surveyvoi.html + Status: 403 + Message: Forbidden **I have checked this URL and can confirm that it is valid.** -# System requirements - -The package has system requirements. Some of these requirements are mandatory -- and are required for successful installation -- and others are optional. To ensure that all mandatory requirements are available on CRAN systems, I have checked the software installed on CRAN's various systems. Briefly, this information was obtained from the [Windows toolchain](https://github.com/r-windows/rtools-packages); [macOS toolchain](https://github.com/R-macos/recipes) toolchains; [rcheckserver Debian meta-package](https://statmath.wu.ac.at/AASC/debian/dists/stable/main/binary-amd64/Packages); and via correspondence with CRAN volunteers. - -Below, I have provided a markdown table detailing whether each system requirement is optional or mandatory under various operating systems. I have also included details and URLs verifying the availability of mandatory system requirements on each of CRAN's systems. Where URLs are provided for certain software on certain operating systems (e.g., for gmpxx on Windows), the URL points directly to the source code for the relevant toolchain (e.g., the RTools for Windows) for including the software. - -| Software | Debian | Fedora | Windows | macOS | -|:--------|:---------:|:--------:|:------:|:------:| -| JAGS (>= 4.3.0) | Optional | Optional |Optional | Optional | -| fftw3 (>= 3.3) | Mandatory (1) | Mandatory (1) | Mandatory (1) | Mandatory (1) | -| gmp (>= 6.2.1) | Mandatory (2) | Mandatory (3) | [Mandatory](https://statmath.wu.ac.at/AASC/debian/dists/stable/main/binary-amd64/Packages) | [Mandatory](https://github.com/r-windows/rtools-packages/blob/master/mingw-w64-gmp/PKGBUILD) | [Mandatory](https://github.com/r-windows/rtools-packages/blob/master/mingw-w64-gmp/PKGBUILD) | [Mandatory](https://github.com/R-macos/recipes/blob/master/recipes/gmp) | -| gmpxx (>= 6.2.1) | [Mandatory (2)](https://statmath.wu.ac.at/AASC/debian/dists/stable/main/binary-amd64/Packages) | Mandatory (3) | [Mandatory](https://github.com/r-windows/rtools-packages/blob/master/mingw-w64-gmp/PKGBUILD) | [Mandatory](https://github.com/R-macos/recipes/blob/master/recipes/gmp) | -| mpfr (>= 4.1.0) | [Mandatory (4)](https://statmath.wu.ac.at/AASC/debian/dists/stable/main/binary-amd64/Packages) | Mandatory (4) | [Mandatory](https://github.com/r-windows/rtools-packages/blob/master/mingw-w64-mpfr/PKGBUILD) | [Mandatory](https://github.com/R-macos/recipes/blob/master/recipes/mpfr) | -| autoconf (>= 2.69) | Optional | Optional | Optional | [Mandatory](https://github.com/R-macos/recipes/blob/master/recipes/autoconf) | -| automake (>= 1.16.5) | Optional | Optional | Optional | [Mandatory](https://github.com/R-macos/recipes/blob/master/recipes/automake) | - -(1) This requirement is available on all of CRAN's servers because the PoissonBinomial R package relies on the fftw3 library as a system requirement and this package passes checks on all systems (see https://cran.r-project.org/package=PoissonBinomial). - -(2) This requirement is available on CRAN's Debian server(s) because it is available via the Debian libgmp3-dev package, and this package is a dependency of the rcheckserver Debian meta-package. - -(3) This requirement is available on CRAN's Fedora server(s) because Prof. Brian Ripely checked that that the gmp-devel RPM is available on each machine (i.e., https://fedora.pkgs.org/35/fedora-x86_64/gmp-devel-6.2.0-7.fc35.i686.rpm.html) (Prof Brian Ripley, personal communication, August 25, 2022). - -(4) This requirement is available on all of CRAN's servers because the Rmpfr R package relies on the mpfr library as a system requirement and this package passes checks on all systems (see https://cran.r-project.org/package=Rmpfr). - # Downstream dependencies There are no existing packages that depend on this package. - -# Comments from CRAN volunteers on previous submissions - -* Correct your SystemRequirements. - - **Thanks for catching this. I have added the C++ bindings for the GMP library (i.e., gmpxx) to the SystemRequirements field, and updated the minimum versions number for gmp and gmpxx.** - -* Correct your configure script (see 'Writing R Extensions' for recommendations for using autoconf to write a *reliable* script, including logging what it does). - - **Thank you for the suggestion. I have updated the configure script to use autoconf and provide logging.** - -* Inform the maintainers of binary packages, as this is a new -requirement on external software. It seems the macOS ones are not built -with C++ bindings (and you could and should have checked for yourself -from the published 'recipes' at https://github.com/R-macos/recipes). - - **Thank you very much for this advice. I am sorry that I did not check these requirements prior to my previous submission. After submitting a pull request to the maintainer of the macOS binary package (https://github.com/R-macos/recipes/pull/19), the macOS libraries now include C++ bindings for GMP. I have also confirmed with the maintainer of the Windows binary packages that the C++ bindings for GMP are available via Rtools (https://github.com/rwinlib/utils/issues/1#issuecomment-912371834). Additionally, to ensure that outdated versions of GMP do not cause issues on Windows systems, the package now uses the RWinLib infrastructure to obtain recent versions of gmp and gmpxx (https://github.com/rwinlib/gmp), see `tools/winlibs.R`). Since the package passes checks on the WinBuilder and macOS builder platforms, I am hopeful that these issues have been resolved.** - -* Please always add all authors, contributors and copyright holders in the Authors@R field with the appropriate roles. e.g.: Free Software Foundation, Inc. Please explain in the submission comments what you did about this issue. - - **This comment was raised on a previous submission wherein the Free Software Foundation was listed as a copyright holder. Previously, the foundation was listed a copyright holder because the package contained a header file from the gmp library to help ensure that dependencies were available. Since the dependencies should now all be available on CRAN's systems, the header file has been removed and, as such, the foundation has been removed as a copyright holder.** diff --git a/docs/404.html b/docs/404.html index 8cb2494..5fd401f 100644 --- a/docs/404.html +++ b/docs/404.html @@ -32,7 +32,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/articles/index.html b/docs/articles/index.html index 260a8bf..9af3f03 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/articles/surveyvoi.html b/docs/articles/surveyvoi.html index d8c19e2..9d36679 100644 --- a/docs/articles/surveyvoi.html +++ b/docs/articles/surveyvoi.html @@ -33,7 +33,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -72,7 +72,7 @@

surveyvoi: Survey Value of Information

Jeffrey O. Hanson

-

2023-02-24

+

2024-02-14

Source: vignettes/surveyvoi.Rmd @@ -85,7 +85,7 @@

2023-02-24

Introduction

The funding available for conservation is limited. To ensure that conservation funds are allocated cost-effectively, conservation plans (termed prioritizations) can be developed – using a combination of economic, biodiversity, and land-use data – to prioritize a set of sites for conservation management (e.g. protected area establishment). However, existing data on biodiversity patterns are incomplete. As a consequence, prioritizations can potentially be improved by collecting additional data. Specifically, ecological surveys can be conducted in sites to learn more about which species are present within them. However, conducting ecological surveys reduces the funds available for conservation management. Thus, decision makers need to strategically allocate funding for surveying sites and managing them for conservation—this is not a trivial task.

-

The surveyvoi R package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management – wherein some sites have previously been surveyed and other sites have not – it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the ‘Gurobi’ optimization software (available from https://www.gurobi.com) and the gurobi R package (installation instructions available for Linux, Windows, and Mac OS).

+

The surveyvoi R package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management – wherein some sites have previously been surveyed and other sites have not – it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the ‘Gurobi’ optimization software (available from https://www.gurobi.com) and the gurobi R package (installation instructions available for online Linux, Windows, and Mac OS).

This tutorial provides a brief overview of the surveyvoi R package. Here, we will simulate survey data, fit statistical models to characterize the spatial distribution of a simulated species, and generate and evaluate survey schemes based on different approaches. Although this tutorial deals with only a single simulated species – to keep the tutorial simple and reduce computational burden – the functions used in this tutorial are designed to work with multiple species. If you want to learn more about a specific function, please consult the documentation written specifically for the function (accessible using the R code ?function, where function is the name of desired function).

@@ -151,7 +151,7 @@

Simulate data## 8 (0.590849 0.748232) ## 9 (0.373888 0.150227) ## 10 (0.141298 0.307626) -## # … with 20 more rows +## # ℹ 20 more rows 
 # plot the spatial location of the sites
 ggplot(site_data) +
@@ -303,7 +303,7 @@ 
Modeling probability of occupancy##  8 0.565847
 ##  9 0.452463
 ## 10 0.565847
-## # … with 20 more rows
+## # ℹ 20 more rows 
 site_data$p1 <- xgb_predictions$f1
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--- a/docs/authors.html
+++ b/docs/authors.html
@@ -17,7 +17,7 @@
       
       
         surveyvoi
-        1.0.5.1
+        1.0.6
diff --git a/docs/index.html b/docs/index.html index d3820e5..c6d42b1 100644 --- a/docs/index.html +++ b/docs/index.html @@ -46,7 +46,7 @@ surveyvoi - 1.0.5.1 + 1.0.6
diff --git a/docs/news/index.html b/docs/news/index.html index 2fd01ba..7b47a56 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6

@@ -50,6 +50,12 @@

Changelog

Source: NEWS.md +
+

surveyvoi 1.0.6

+
  • Fix installation for Windows on arm64 (#50).
    • +
  • Fix aliasing for package overview help file (#49).
    • +
  • Remove CXX specification in Makevars to avoid NOTEs in package checks.
    • +

surveyvoi 1.0.5.1

  • Update citation.
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 386449a..39fd920 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.0.7 pkgdown_sha: ~ articles: surveyvoi: surveyvoi.html -last_built: 2023-02-24T01:05Z +last_built: 2024-02-14T22:16Z urls: reference: https://github.com/prioritizr/surveyvoi/reference article: https://github.com/prioritizr/surveyvoi/articles diff --git a/docs/reference/approx_evdsi.html b/docs/reference/approx_evdsi.html index 2aeeda4..06eddb6 100644 --- a/docs/reference/approx_evdsi.html +++ b/docs/reference/approx_evdsi.html @@ -21,7 +21,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -298,27 +298,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # set total budget for managing sites for conservation # (i.e. 50% of the cost of managing all sites) diff --git a/docs/reference/approx_near_optimal_survey_scheme.html b/docs/reference/approx_near_optimal_survey_scheme.html index 257e7e3..6d807c5 100644 --- a/docs/reference/approx_near_optimal_survey_scheme.html +++ b/docs/reference/approx_near_optimal_survey_scheme.html @@ -20,7 +20,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -358,27 +358,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # set total budget for managing sites for conservation # (i.e. 50% of the cost of managing all sites) diff --git a/docs/reference/approx_optimal_survey_scheme.html b/docs/reference/approx_optimal_survey_scheme.html index c5677b5..c7577c4 100644 --- a/docs/reference/approx_optimal_survey_scheme.html +++ b/docs/reference/approx_optimal_survey_scheme.html @@ -19,7 +19,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -320,7 +320,8 @@

Dependencies

Please note that this function requires the Gurobi optimization software (https://www.gurobi.com/) and the gurobi R package if different sites have different survey costs. Installation instruction are available -online for for Linux, Windows, and Mac OS.

+online for Linux, Windows, and Mac OS +(see https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer).

@@ -337,27 +338,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # set total budget for managing sites for conservation # (i.e. 50% of the cost of managing all sites) diff --git a/docs/reference/env_div_survey_scheme.html b/docs/reference/env_div_survey_scheme.html index c8b8492..fe560d9 100644 --- a/docs/reference/env_div_survey_scheme.html +++ b/docs/reference/env_div_survey_scheme.html @@ -18,7 +18,7 @@ surveyvoi - 1.0.5.1 + 1.0.6
@@ -170,7 +170,7 @@

Solver

install the Gurobi optimization software and the gurobi R package because it can generate survey schemes much faster. Note that special academic licenses are available at no cost. -Installation instructions are available online for Linux, Windows, and Mac OS operating systems.

+Installation instructions are available online for Linux, Windows, and Mac OS operating systems.

References

diff --git a/docs/reference/evdci.html b/docs/reference/evdci.html index cb32ce6..32b7ceb 100644 --- a/docs/reference/evdci.html +++ b/docs/reference/evdci.html @@ -20,7 +20,7 @@ surveyvoi - 1.0.5.1 + 1.0.6
@@ -244,27 +244,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # set total budget for managing sites for conservation # (i.e. 50% of the cost of managing all sites) diff --git a/docs/reference/evdsi.html b/docs/reference/evdsi.html index 5c8c490..5acb3f4 100644 --- a/docs/reference/evdsi.html +++ b/docs/reference/evdsi.html @@ -20,7 +20,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -274,27 +274,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # set total budget for managing sites for conservation # (i.e. 50% of the cost of managing all sites) diff --git a/docs/reference/feasible_survey_schemes.html b/docs/reference/feasible_survey_schemes.html index fb1f22f..de3829e 100644 --- a/docs/reference/feasible_survey_schemes.html +++ b/docs/reference/feasible_survey_schemes.html @@ -18,7 +18,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -125,7 +125,8 @@

Dependencies

Please note that this function requires the Gurobi optimization software (https://www.gurobi.com/) and the gurobi R package if different sites have different survey costs. Installation instruction are available -online for for Linux, Windows, and Mac OS.

+online for Linux, Windows, and Mac OS +(see https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer).

diff --git a/docs/reference/figures/README-f_plot-1.png b/docs/reference/figures/README-f_plot-1.png index 4d01fc3..877f57c 100644 Binary files a/docs/reference/figures/README-f_plot-1.png and b/docs/reference/figures/README-f_plot-1.png differ diff --git a/docs/reference/figures/README-n_plot-1.png b/docs/reference/figures/README-n_plot-1.png index b996b61..382fb91 100644 Binary files a/docs/reference/figures/README-n_plot-1.png and b/docs/reference/figures/README-n_plot-1.png differ diff --git a/docs/reference/figures/README-p_plot-1.png b/docs/reference/figures/README-p_plot-1.png index e39d618..06e3ae1 100644 Binary files a/docs/reference/figures/README-p_plot-1.png and b/docs/reference/figures/README-p_plot-1.png differ diff --git a/docs/reference/figures/README-unnamed-chunk-10-1.png b/docs/reference/figures/README-unnamed-chunk-10-1.png index ba3e694..bdb9fa3 100644 Binary files a/docs/reference/figures/README-unnamed-chunk-10-1.png and b/docs/reference/figures/README-unnamed-chunk-10-1.png differ diff --git a/docs/reference/figures/README-unnamed-chunk-6-1.png b/docs/reference/figures/README-unnamed-chunk-6-1.png index b4a5147..979b54e 100644 Binary files a/docs/reference/figures/README-unnamed-chunk-6-1.png and b/docs/reference/figures/README-unnamed-chunk-6-1.png differ diff --git a/docs/reference/figures/README-unnamed-chunk-6-2.png b/docs/reference/figures/README-unnamed-chunk-6-2.png index fed8029..b27de80 100644 Binary files a/docs/reference/figures/README-unnamed-chunk-6-2.png and b/docs/reference/figures/README-unnamed-chunk-6-2.png differ diff --git a/docs/reference/fit_hglm_occupancy_models.html b/docs/reference/fit_hglm_occupancy_models.html index 31d79e3..e7581c2 100644 --- a/docs/reference/fit_hglm_occupancy_models.html +++ b/docs/reference/fit_hglm_occupancy_models.html @@ -23,7 +23,7 @@ surveyvoi - 1.0.5.1 + 1.0.6
@@ -738,7 +738,7 @@

Examples

#> 8 9.97e- 1 0.0608 #> 9 1.89e- 4 0.999 #> 10 2.89e- 1 0.829 -#> # … with 20 more rows +#> # ℹ 20 more rows # print model performance print(results$performance, width = Inf) diff --git a/docs/reference/fit_xgb_occupancy_models.html b/docs/reference/fit_xgb_occupancy_models.html index adf1f5d..790875b 100644 --- a/docs/reference/fit_xgb_occupancy_models.html +++ b/docs/reference/fit_xgb_occupancy_models.html @@ -19,7 +19,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -370,7 +370,7 @@

Examples

#> 8 0.549 0.627 #> 9 0.450 0.630 #> 10 0.529 0.557 -#> # … with 20 more rows +#> # ℹ 20 more rows # print model performance print(results$performance, width = Inf) diff --git a/docs/reference/geo_cov_survey_scheme.html b/docs/reference/geo_cov_survey_scheme.html index 5a8de75..4d74d81 100644 --- a/docs/reference/geo_cov_survey_scheme.html +++ b/docs/reference/geo_cov_survey_scheme.html @@ -18,7 +18,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -152,7 +152,7 @@

Solver

install the Gurobi optimization software and the gurobi R package because it can generate survey schemes much faster. Note that special academic licenses are available at no cost. -Installation instructions are available online for Linux, Windows, and Mac OS operating systems.

+Installation instructions are available online for Linux, Windows, and Mac OS operating systems.

References

diff --git a/docs/reference/index.html b/docs/reference/index.html index eddbcae..42ecb1d 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6
@@ -54,7 +54,7 @@

Summary

surveyvoi

+

surveyvoi surveyvoi-package

surveyvoi: Survey Value of Information

diff --git a/docs/reference/n_states.html b/docs/reference/n_states.html index 3063e68..47658c6 100644 --- a/docs/reference/n_states.html +++ b/docs/reference/n_states.html @@ -18,7 +18,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/reference/optimal_survey_scheme.html b/docs/reference/optimal_survey_scheme.html index 5a00c66..666a002 100644 --- a/docs/reference/optimal_survey_scheme.html +++ b/docs/reference/optimal_survey_scheme.html @@ -19,7 +19,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -295,7 +295,8 @@

Dependencies

Please note that this function requires the Gurobi optimization software (https://www.gurobi.com/) and the gurobi R package if different sites have different survey costs. Installation instruction are available -online for for Linux, Windows, and Mac OS.

+online for Linux, Windows, and Mac OS +(see https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer).

@@ -312,27 +313,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # set total budget for managing sites for conservation # (i.e. 50% of the cost of managing all sites) diff --git a/docs/reference/prior_probability_matrix.html b/docs/reference/prior_probability_matrix.html index 54f6cfa..bb4b441 100644 --- a/docs/reference/prior_probability_matrix.html +++ b/docs/reference/prior_probability_matrix.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6
@@ -171,27 +171,26 @@

Examples

#> Bounding box: xmin: 0.10513 ymin: 0.04556193 xmax: 0.9764926 ymax: 0.8637977 #> CRS: NA #> # A tibble: 6 × 14 -#> surve…¹ manag…² f1 f2 f3 n1 n2 n3 e1 e2 p1 p2 -#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 1 0.999 -#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 0 0 -#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 1 0.419 -#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 0.022 0.502 -#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 0.318 0.13 -#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 0.474 0.997 -#> # … with 2 more variables: p3 <dbl>, geometry <POINT>, and abbreviated variable -#> # names ¹​survey_cost, ²​management_cost +#> survey_cost management_cost f1 f2 f3 n1 n2 n3 e1 e2 +#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 14 102 1 1 1 3 3 3 1.00 -0.848 +#> 2 25 90 0 0 0 0 0 0 -1.44 1.27 +#> 3 25 165 1 0.6 0 5 5 5 1.25 0.817 +#> 4 17 104 0 0 0 0 0 0 -0.484 -0.292 +#> 5 18 100 0 0 0 0 0 0 0.0135 0.380 +#> 6 15 94 0 0 0 0 0 0 -0.347 -1.33 +#> # ℹ 4 more variables: p1 <dbl>, p2 <dbl>, p3 <dbl>, geometry <POINT> # load example feature data data(sim_features) print(sim_features) #> # A tibble: 3 × 7 -#> name survey survey_sensitivity survey_specificity model_sens…¹ model…² target -#> <chr> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 f1 TRUE 0.954 0.886 0.718 0.811 1 -#> 2 f2 TRUE 0.974 0.875 0.705 0.860 1 -#> 3 f3 TRUE 0.956 0.823 0.768 0.887 1 -#> # … with abbreviated variable names ¹​model_sensitivity, ²​model_specificity +#> name survey survey_sensitivity survey_specificity model_sensitivity +#> <chr> <lgl> <dbl> <dbl> <dbl> +#> 1 f1 TRUE 0.954 0.886 0.718 +#> 2 f2 TRUE 0.974 0.875 0.705 +#> 3 f3 TRUE 0.956 0.823 0.768 +#> # ℹ 2 more variables: model_specificity <dbl>, target <dbl> # calculate prior probability matrix prior_matrix <- prior_probability_matrix( diff --git a/docs/reference/relative_site_richness_scores.html b/docs/reference/relative_site_richness_scores.html index ef79e1d..35c14d3 100644 --- a/docs/reference/relative_site_richness_scores.html +++ b/docs/reference/relative_site_richness_scores.html @@ -20,7 +20,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/reference/relative_site_uncertainty_scores.html b/docs/reference/relative_site_uncertainty_scores.html index cd2cba1..660d66a 100644 --- a/docs/reference/relative_site_uncertainty_scores.html +++ b/docs/reference/relative_site_uncertainty_scores.html @@ -21,7 +21,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/reference/sim_data.html b/docs/reference/sim_data.html index edf7468..063e2d6 100644 --- a/docs/reference/sim_data.html +++ b/docs/reference/sim_data.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/reference/simulate_feature_data.html b/docs/reference/simulate_feature_data.html index b35ee25..41cdbf7 100644 --- a/docs/reference/simulate_feature_data.html +++ b/docs/reference/simulate_feature_data.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/reference/simulate_site_data.html b/docs/reference/simulate_site_data.html index 2dea6fe..84f1fd3 100644 --- a/docs/reference/simulate_site_data.html +++ b/docs/reference/simulate_site_data.html @@ -17,7 +17,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 diff --git a/docs/reference/surveyvoi.html b/docs/reference/surveyvoi.html index 932519f..296c914 100644 --- a/docs/reference/surveyvoi.html +++ b/docs/reference/surveyvoi.html @@ -28,7 +28,7 @@ surveyvoi - 1.0.5.1 + 1.0.6 @@ -82,8 +82,8 @@

surveyvoi: Survey Value of Information

Details

Please note that several functions depend on the 'Gurobi' optimization software (available from https://www.gurobi.com) -and the gurobi R package (installation instructions available for -Linux, Windows, and Mac OS). +and the gurobi R package (installation instructions +available online for Linux, Windows, and Mac OS). Additionally, the JAGS software (available from https://mcmc-jags.sourceforge.io/) is required to fit hierarchical generalized linear models.

@@ -93,6 +93,13 @@

See also

The package vignette provides a tutorial (accessible using the code vignettes("surveyvoi")).

+
+

Author

+

Package authors:

@@ -161,7 +161,7 @@

Solver

install the Gurobi optimization software and the gurobi R package because it can generate survey schemes much faster. Note that special academic licenses are available at no cost. -Installation instructions are available online for Linux, Windows, and Mac OS operating systems.

+Installation instructions are available online for Linux, Windows, and Mac OS operating systems.

diff --git a/inst/doc/surveyvoi.Rmd b/inst/doc/surveyvoi.Rmd index 164ea9b..b21c3e8 100644 --- a/inst/doc/surveyvoi.Rmd +++ b/inst/doc/surveyvoi.Rmd @@ -41,7 +41,7 @@ devtools::load_all() The funding available for conservation is limited. To ensure that conservation funds are allocated cost-effectively, conservation plans (termed prioritizations) can be developed -- using a combination of economic, biodiversity, and land-use data -- to prioritize a set of sites for conservation management (e.g. protected area establishment). However, existing data on biodiversity patterns are incomplete. As a consequence, prioritizations can potentially be improved by collecting additional data. Specifically, ecological surveys can be conducted in sites to learn more about which species are present within them. However, conducting ecological surveys reduces the funds available for conservation management. Thus, decision makers need to strategically allocate funding for surveying sites and managing them for conservation---this is not a trivial task. -The _surveyvoi R_ package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management -- wherein some sites have previously been surveyed and other sites have not -- it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the 'Gurobi' optimization software (available from ) and the _gurobi R_ package (installation instructions available for [Linux](https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html), [Windows](https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html), and [Mac OS](https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html)). +The _surveyvoi R_ package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management -- wherein some sites have previously been surveyed and other sites have not -- it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the 'Gurobi' optimization software (available from ) and the _gurobi R_ package ([installation instructions available for online Linux, Windows, and Mac OS](https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer)). This tutorial provides a brief overview of the _surveyvoi R_ package. Here, we will simulate survey data, fit statistical models to characterize the spatial distribution of a simulated species, and generate and evaluate survey schemes based on different approaches. Although this tutorial deals with only a single simulated species -- to keep the tutorial simple and reduce computational burden -- the functions used in this tutorial are designed to work with multiple species. If you want to learn more about a specific function, please consult the documentation written specifically for the function (accessible using the R code `?function`, where `function` is the name of desired function). diff --git a/inst/doc/surveyvoi.html b/inst/doc/surveyvoi.html index db0c529..42e4858 100644 --- a/inst/doc/surveyvoi.html +++ b/inst/doc/surveyvoi.html @@ -12,7 +12,7 @@ - + surveyvoi: Survey Value of Information @@ -171,7 +171,7 @@

surveyvoi: Survey Value of Information

Jeffrey O. Hanson

-

2023-02-24

+

2024-02-14

@@ -192,7 +192,7 @@

2023-02-24

Introduction

The funding available for conservation is limited. To ensure that conservation funds are allocated cost-effectively, conservation plans (termed prioritizations) can be developed – using a combination of economic, biodiversity, and land-use data – to prioritize a set of sites for conservation management (e.g. protected area establishment). However, existing data on biodiversity patterns are incomplete. As a consequence, prioritizations can potentially be improved by collecting additional data. Specifically, ecological surveys can be conducted in sites to learn more about which species are present within them. However, conducting ecological surveys reduces the funds available for conservation management. Thus, decision makers need to strategically allocate funding for surveying sites and managing them for conservation—this is not a trivial task.

-

The surveyvoi R package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management – wherein some sites have previously been surveyed and other sites have not – it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the ‘Gurobi’ optimization software (available from https://www.gurobi.com) and the gurobi R package (installation instructions available for Linux, Windows, and Mac OS).

+

The surveyvoi R package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management – wherein some sites have previously been surveyed and other sites have not – it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the ‘Gurobi’ optimization software (available from https://www.gurobi.com) and the gurobi R package (installation instructions available for online Linux, Windows, and Mac OS).

This tutorial provides a brief overview of the surveyvoi R package. Here, we will simulate survey data, fit statistical models to characterize the spatial distribution of a simulated species, and generate and evaluate survey schemes based on different approaches. Although this tutorial deals with only a single simulated species – to keep the tutorial simple and reduce computational burden – the functions used in this tutorial are designed to work with multiple species. If you want to learn more about a specific function, please consult the documentation written specifically for the function (accessible using the R code ?function, where function is the name of desired function).

@@ -254,13 +254,13 @@

Simulate data

## 8 (0.590849 0.748232) ## 9 (0.373888 0.150227) ## 10 (0.141298 0.307626) -## # … with 20 more rows +## # ℹ 20 more rows 
# plot the spatial location of the sites
 ggplot(site_data) +
   geom_sf() +
   ggtitle("Sites") +
   labs(x = "X coordinate", y = "Y coordinate")
-

+

The site_data object is a spatially explicit dataset (i.e. sf object) that contains information on the site locations and additional site attributes. Here, each row corresponds to a different site, and each column contains a different site attribute. The f1 column contains the results from previous surveys, where values describe the proportion of previous surveys where species were previously detected at each site. Since each site has had at most a single previous survey, these data contain zeros (indicating that the species has not been detected) and ones (indicating that the species has been detected). The n1 column contains the number of previous surveys conducted within each site. Thus, sites with zeros in this column have not previously been surveyed. The e1, e2, and e3 columns contain environmental information for each site (e.g. normalized temperature and rainfall data). The survey_cost column contains the cost of surveying each site, and the management_cost column contains the cost of managing each site for conservation.

To help understand the simulated data, let’s create some visualizations.

# plot site occupancy data from previous surveys
@@ -276,7 +276,7 @@ 
Simulate data

     facet_wrap(~ name) +
     labs(title = "Detection/non-detection data",
          x = "X coordinate", y = "Y coordinate")
-

+

# plot number of previous surveys within each site
 site_data %>%
   select(starts_with("n")) %>%
@@ -288,7 +288,7 @@ 
Simulate data

     facet_wrap(~ name) +
     labs(title = "Number of previous surveys",
          x = "X coordinate", y = "Y coordinate")
-

+

# plot site cost data
 # note that survey and management costs are on different scales
 p1 <- ggplot(site_data) +
@@ -302,7 +302,7 @@ 
Simulate data

       labs(title = "Management cost", x = "X coordinate", y = "Y coordinate") +
       theme(legend.title = element_blank())
 grid.arrange(p1, p2, nrow = 1)
-

+

# plot site environmental data
 site_data %>%
   select(starts_with("e")) %>%
@@ -313,7 +313,7 @@ 
Simulate data

     scale_color_viridis() +
     labs(title = "Environmental conditions",
          x = "X coordinate", y = "Y coordinate")
-

+

After simulating data for the sites, we will simulate data for the conservation feature. We set proportion_of_survey_features = 1 to indicate that this feature will be examined in future surveys.

# simulate feature data
 feature_data <- simulate_feature_data(
@@ -395,7 +395,7 @@ 
Modeling probability of occupancy

 ##  8 0.565847
 ##  9 0.452463
 ## 10 0.565847
-## # … with 20 more rows
+## # ℹ 20 more rows 
site_data$p1 <- xgb_predictions$f1
# plot site-level estimated occupancy probabilities
 site_data %>%
@@ -406,7 +406,7 @@ 
Modeling probability of occupancy

   facet_wrap(~name) +
   scale_color_viridis() +
   labs(title = "Modeled probabilities", x = "X coordinate", y = "Y coordinate")
-

+

Expected value given current information

@@ -525,7 +525,7 @@

Survey schemes

facet_wrap(~ name, nrow = 2) + scale_color_manual(values = c("TRUE" = "red", "FALSE" = "black")) + labs(x = "X coordinate", y = "Y coordinate")
-

+

We can see that different approaches yield different survey schemes – but how well do they perform?

@@ -638,7 +638,7 @@

Optimized survey scheme

facet_wrap(~ name, nrow = 1) + scale_color_manual(values = c("TRUE" = "red", "FALSE" = "black")) + labs(x = "X coordinate", y = "Y coordinate")
-

+

We can see that the optimized survey scheme (opt_scheme) is different to the previous survey schemes.

# calculate expected value of sample information for the optimized scheme
 evd_opt <- evdsi(
diff --git a/man/approx_optimal_survey_scheme.Rd b/man/approx_optimal_survey_scheme.Rd
index 84fc565..3144abc 100644
--- a/man/approx_optimal_survey_scheme.Rd
+++ b/man/approx_optimal_survey_scheme.Rd
@@ -208,7 +208,8 @@ this algorithm, it can take a very long time to complete.
 Please note that this function requires the Gurobi optimization software
 (\url{https://www.gurobi.com/}) and the \pkg{gurobi} R package if different
 sites have different survey costs. Installation instruction are available
-online for for \href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS}.
+online for Linux, Windows, and Mac OS
+(see \url{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}).
 }
 
 \examples{
diff --git a/man/env_div_survey_scheme.Rd b/man/env_div_survey_scheme.Rd
index 6c5f5c9..64e6acb 100644
--- a/man/env_div_survey_scheme.Rd
+++ b/man/env_div_survey_scheme.Rd
@@ -92,7 +92,7 @@ The Comprehensive R Archive Network (CRAN), it is strongly recommended to
 install the \href{https://www.gurobi.com/}{Gurobi optimization software} and the
 \pkg{gurobi} R package because it can generate survey schemes much faster.
 Note that special academic licenses are available at no cost.
-Installation instructions are available online for \href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS} operating systems.
+Installation instructions are \href{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}{available online for Linux, Windows, and Mac OS operating systems}.
 }
 
 \examples{
diff --git a/man/feasible_survey_schemes.Rd b/man/feasible_survey_schemes.Rd
index 04972f4..54201ea 100644
--- a/man/feasible_survey_schemes.Rd
+++ b/man/feasible_survey_schemes.Rd
@@ -56,7 +56,8 @@ survey schemes given survey costs and a fixed budget.
 Please note that this function requires the Gurobi optimization software
 (\url{https://www.gurobi.com/}) and the \pkg{gurobi} R package if different
 sites have different survey costs. Installation instruction are available
-online for for \href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS}.
+online for Linux, Windows, and Mac OS
+(see \url{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}).
 }
 
 \examples{
diff --git a/man/figures/README-f_plot-1.png b/man/figures/README-f_plot-1.png
index 4d01fc3..877f57c 100644
Binary files a/man/figures/README-f_plot-1.png and b/man/figures/README-f_plot-1.png differ
diff --git a/man/figures/README-n_plot-1.png b/man/figures/README-n_plot-1.png
index b996b61..382fb91 100644
Binary files a/man/figures/README-n_plot-1.png and b/man/figures/README-n_plot-1.png differ
diff --git a/man/figures/README-p_plot-1.png b/man/figures/README-p_plot-1.png
index e39d618..06e3ae1 100644
Binary files a/man/figures/README-p_plot-1.png and b/man/figures/README-p_plot-1.png differ
diff --git a/man/figures/README-unnamed-chunk-10-1.png b/man/figures/README-unnamed-chunk-10-1.png
index ba3e694..bdb9fa3 100644
Binary files a/man/figures/README-unnamed-chunk-10-1.png and b/man/figures/README-unnamed-chunk-10-1.png differ
diff --git a/man/figures/README-unnamed-chunk-6-1.png b/man/figures/README-unnamed-chunk-6-1.png
index b4a5147..979b54e 100644
Binary files a/man/figures/README-unnamed-chunk-6-1.png and b/man/figures/README-unnamed-chunk-6-1.png differ
diff --git a/man/figures/README-unnamed-chunk-6-2.png b/man/figures/README-unnamed-chunk-6-2.png
index fed8029..b27de80 100644
Binary files a/man/figures/README-unnamed-chunk-6-2.png and b/man/figures/README-unnamed-chunk-6-2.png differ
diff --git a/man/geo_cov_survey_scheme.Rd b/man/geo_cov_survey_scheme.Rd
index 44e1608..89cfc5b 100644
--- a/man/geo_cov_survey_scheme.Rd
+++ b/man/geo_cov_survey_scheme.Rd
@@ -78,7 +78,7 @@ The Comprehensive R Archive Network (CRAN), it is strongly recommended to
 install the \href{https://www.gurobi.com/}{Gurobi optimization software} and the
 \pkg{gurobi} R package because it can generate survey schemes much faster.
 Note that special academic licenses are available at no cost.
-Installation instructions are available online for \href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS} operating systems.
+Installation instructions are \href{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}{available online for Linux, Windows, and Mac OS operating systems}.
 }
 
 \examples{
diff --git a/man/optimal_survey_scheme.Rd b/man/optimal_survey_scheme.Rd
index f4c366b..096634c 100644
--- a/man/optimal_survey_scheme.Rd
+++ b/man/optimal_survey_scheme.Rd
@@ -190,7 +190,8 @@ this algorithm, it can take a very long time to complete.
 Please note that this function requires the Gurobi optimization software
 (\url{https://www.gurobi.com/}) and the \pkg{gurobi} R package if different
 sites have different survey costs. Installation instruction are available
-online for for \href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS}.
+online for Linux, Windows, and Mac OS
+(see \url{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}).
 }
 
 \examples{
diff --git a/man/surveyvoi.Rd b/man/surveyvoi.Rd
index cfd6ffe..6e8f66d 100644
--- a/man/surveyvoi.Rd
+++ b/man/surveyvoi.Rd
@@ -3,6 +3,7 @@
 \docType{package}
 \name{surveyvoi}
 \alias{surveyvoi}
+\alias{surveyvoi-package}
 \title{surveyvoi: Survey Value of Information}
 \description{
 Decision support tool for prioritizing sites for ecological
@@ -21,8 +22,8 @@ value of information analysis.
 \details{
 Please note that several functions depend on
 the 'Gurobi' optimization software (available from \url{https://www.gurobi.com})
-and the \pkg{gurobi} R package (installation instructions available for
-\href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS}).
+and the \pkg{gurobi} R package (installation instructions
+\href{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}{available online for Linux, Windows, and Mac OS}).
 Additionally, the JAGS software
 (available from \url{https://mcmc-jags.sourceforge.io/}) is required to fit
 hierarchical generalized linear models.
@@ -31,3 +32,12 @@ hierarchical generalized linear models.
 The package vignette provides a tutorial
 (accessible using the code \code{vignettes("surveyvoi")}).
 }
+\author{
+Package authors:
+\itemize{
+\item Jeffrey O. Hanson \email{jeffrey.hanson@uqconnect.edu.au} \href{https://orcid.org/0000-0002-4716-6134}{ORCID}
+\item Iadine Chadès \email{iadine.chades@csiro.au} \href{https://orcid.org/0000-0002-7442-2850}{ORCID}
+\item Emma J. Hudgins \email{emma.hudgins@mail.mcgill.ca} \href{https://orcid.org/0000-0002-8402-5111}{ORCID}
+\item Joseph R. Bennett \email{joseph.bennett@carleton.ca} \href{https://orcid.org/0000-0002-3901-9513}{ORCID}
+}
+}
diff --git a/man/weighted_survey_scheme.Rd b/man/weighted_survey_scheme.Rd
index 5c1521a..4957e1d 100644
--- a/man/weighted_survey_scheme.Rd
+++ b/man/weighted_survey_scheme.Rd
@@ -89,7 +89,7 @@ The Comprehensive R Archive Network (CRAN), it is strongly recommended to
 install the \href{https://www.gurobi.com/}{Gurobi optimization software} and the
 \pkg{gurobi} R package because it can generate survey schemes much faster.
 Note that special academic licenses are available at no cost.
-Installation instructions are available online for \href{https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html}{Linux}, \href{https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html}{Windows}, and \href{https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html}{Mac OS} operating systems.
+Installation instructions are \href{https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer}{available online for Linux, Windows, and Mac OS operating systems}.
 }
 
 \examples{
diff --git a/src/Makevars.in b/src/Makevars.in
index 2aefe17..f4cf9cb 100644
--- a/src/Makevars.in
+++ b/src/Makevars.in
@@ -1,4 +1,3 @@
-CXX_STD = CXX11
 PKG_CPPFLAGS = @PKG_CPPFLAGS@
 PKG_LIBS = @PKG_LIBS@
 
diff --git a/src/Makevars.win b/src/Makevars.win
index ccadb75..ebe2af0 100644
--- a/src/Makevars.win
+++ b/src/Makevars.win
@@ -2,8 +2,6 @@ VERSION = 6.1.2
 RWINLIB = ../windows/gmp-$(VERSION)
 BUILD = ${subst gcc ,-,${R_COMPILED_BY}}
 
-CXX_STD = CXX11
-
 # PKG_CXXFLAGS = -Wno-ignored-attributes              # uncomment for debugging
 
 PKG_CPPFLAGS = -I$(RWINLIB)/include
diff --git a/vignettes/surveyvoi.Rmd b/vignettes/surveyvoi.Rmd
index 164ea9b..b21c3e8 100644
--- a/vignettes/surveyvoi.Rmd
+++ b/vignettes/surveyvoi.Rmd
@@ -41,7 +41,7 @@ devtools::load_all()
 
 The funding available for conservation is limited. To ensure that conservation funds are allocated cost-effectively, conservation plans (termed prioritizations) can be developed -- using a combination of economic, biodiversity, and land-use data -- to prioritize a set of sites for conservation management (e.g. protected area establishment). However, existing data on biodiversity patterns are incomplete. As a consequence, prioritizations can potentially be improved by collecting additional data. Specifically, ecological surveys can be conducted in sites to learn more about which species are present within them. However, conducting ecological surveys reduces the funds available for conservation management. Thus, decision makers need to strategically allocate funding for surveying sites and managing them for conservation---this is not a trivial task.
 
-The _surveyvoi R_ package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management -- wherein some sites have previously been surveyed and other sites have not -- it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the 'Gurobi' optimization software (available from ) and the _gurobi R_ package (installation instructions available for [Linux](https://www.gurobi.com/documentation/9.1/quickstart_linux/r_ins_the_r_package.html), [Windows](https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html), and [Mac OS](https://www.gurobi.com/documentation/9.1/quickstart_mac/r_ins_the_r_package.html)).
+The _surveyvoi R_ package is a decision support tool for prioritizing sites for ecological surveys based on their potential to improve plans for conserving biodiversity (e.g. plans for establishing protected areas). Given a set of sites that could potentially be acquired for conservation management -- wherein some sites have previously been surveyed and other sites have not -- it can be used to generate and evaluate plans for additional surveys. Specifically, plans for ecological surveys can be generated using various conventional approaches (e.g. maximizing expected species richness, geographic coverage, diversity of sampled environmental conditions) and directly maximizing value of information using optimization algorithms. After generating plans for surveys, they can also be evaluated using value of information analysis. Please note that several functions depend on the 'Gurobi' optimization software (available from ) and the _gurobi R_ package ([installation instructions available for online Linux, Windows, and Mac OS](https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer)).
 
 This tutorial provides a brief overview of the _surveyvoi R_ package. Here, we will simulate survey data, fit statistical models to characterize the spatial distribution of a simulated species, and generate and evaluate survey schemes based on different approaches. Although this tutorial deals with only a single simulated species -- to keep the tutorial simple and reduce computational burden -- the functions used in this tutorial are designed to work with multiple species. If you want to learn more about a specific function, please consult the documentation written specifically for the function (accessible using the R code `?function`, where `function` is the name of desired function).