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prioritizr · Feb 14, 2024 · 84018d8 · 84018d8
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diff --git 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, Windows, and Mac OS operating systems](https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer-).
+#'   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
@@ -24,7 +24,7 @@ NULL
 #' (<https://www.gurobi.com/>) and the \pkg{gurobi} R package if different
 #' sites have different survey costs. Installation instruction are available
 #' online for Linux, Windows, and Mac OS
-#' (see <https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer->).
+#' (see <https://support.gurobi.com/hc/en-us/articles/4534161999889-How-do-I-install-Gurobi-Optimizer>).
 #'
 #' @examples
 #' \dontrun{

diff --git a/R/package.R b/R/package.R
@@ -28,7 +28,7 @@ NULL
 #' Please note that several functions depend on
 #' the 'Gurobi' optimization software (available from <https://www.gurobi.com>)
 #' 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-)).
+#' [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 <https://mcmc-jags.sourceforge.io/>) is required to fit
 #' hierarchical generalized linear models.
@@ -38,9 +38,16 @@ NULL
 #' (accessible using the code `vignettes("surveyvoi")`).
 #'
 #' @name surveyvoi
-#' @docType package
+#'
 #' @aliases surveyvoi-package
-NULL
+#'
+#' @author
+#' Package authors:
+#' * Jeffrey O. Hanson \email{[email protected]} [ORCID](https://orcid.org/0000-0002-4716-6134)
+#' * Iadine Chadès \email{[email protected]} [ORCID](https://orcid.org/0000-0002-7442-2850)
+#' * Emma J. Hudgins \email{[email protected]} [ORCID](https://orcid.org/0000-0002-8402-5111)
+#' * Joseph R. Bennett \email{[email protected]} [ORCID](https://orcid.org/0000-0002-3901-9513)
+"_PACKAGE"
 
 # ensure package checks pass
 #' @importFrom utils zip

diff --git a/docs/articles/surveyvoi.html b/docs/articles/surveyvoi.html
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
@@ -3,7 +3,7 @@ pkgdown: 2.0.7
 pkgdown_sha: ~
 articles:
   surveyvoi: surveyvoi.html
-last_built: 2024-01-26T01:55Z
+last_built: 2024-02-14T04:07Z
 urls:
   reference: https://github.com/prioritizr/surveyvoi/reference
   article: https://github.com/prioritizr/surveyvoi/articles

diff --git a/docs/reference/approx_optimal_survey_scheme.html b/docs/reference/approx_optimal_survey_scheme.html
diff --git a/docs/reference/env_div_survey_scheme.html b/docs/reference/env_div_survey_scheme.html
diff --git a/docs/reference/feasible_survey_schemes.html b/docs/reference/feasible_survey_schemes.html
diff --git a/docs/reference/geo_cov_survey_scheme.html b/docs/reference/geo_cov_survey_scheme.html
diff --git a/docs/reference/optimal_survey_scheme.html b/docs/reference/optimal_survey_scheme.html
diff --git a/docs/reference/surveyvoi.html b/docs/reference/surveyvoi.html
diff --git a/docs/reference/weighted_survey_scheme.html b/docs/reference/weighted_survey_scheme.html
diff --git 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 <https://www.gurobi.com>) 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-)).
+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](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).