v0.8.0

DESCRIPTION

@@ -13,11 +13,10 @@ LazyData: true
 RoxygenNote: 7.1.1
 URL: https://www.doserlab.com/files/spoccupancy-web,
         https://groups.google.com/g/spocc-spabund-users,
-        https://github.com/doserjef/spOccupancy
-BugReports: https://github.com/doserjef/spOccupancy/issues
+        https://github.com/biodiverse/spOccupancy
+BugReports: https://github.com/biodiverse/spOccupancy/issues
 Depends: R (>= 3.5.0)
 Imports: stats, coda, abind, RANN, lme4, foreach, doParallel, doRNG,
         parallel, spAbundance, methods
 Suggests: testthat
 NeedsCompilation: yes
-Packaged: 2024-08-02 12:23:51 UTC; jeff

NEWS.md

@@ -97,15 +97,15 @@ spOccupancy v0.5.0 contains numerous substantial updates that provide new functi
 + New functionality for fitting spatially-varying coefficient occupancy models. The function `svcPGOcc()` fits a single-season spatially-varying coefficient model, and `svcTPGOcc()` fits a multi-season spatially-varying coefficient model. We also include the functions `svcPGBinom()` and `svcTPGBinom()` for fitting spatially-varying coefficient generalized linear models when ignoring imperfect detection. We also include the helper function `getSVCSamples()` to more easily extract the SVC samples from the resulting model objects if they are desired.
 + Updated the underlying `C++` code to reduce run times for models that include unstructured random intercepts. 
 + Added the `k.fold.only` argument to all model-fitting functions, which allows users to only perform k-fold cross-validation instead of having to run the model first with the entire data set.
-+ Adjusted how random intercepts in the detection model were being calculated, which resulted in unnecessary massive objects when fitting a model with a large number of random effect levels and spatial locations. See [GitHub issue 14](https://github.com/doserjef/spOccupancy/issues/14). 
-+ Fixed a bug that prevented prediction from working for multi-species models when `X.0` was supplied as a data frame and not a matrix. See [GitHub issue 13](https://github.com/doserjef/spOccupancy/issues/13).
-+ Fixed an error that occurred when the detection-nondetection data were specified in a specific way. See [GitHub issue 12](https://github.com/doserjef/spOccupancy/issues/12).
++ Adjusted how random intercepts in the detection model were being calculated, which resulted in unnecessary massive objects when fitting a model with a large number of random effect levels and spatial locations. See [GitHub issue 14](https://github.com/biodiverse/spOccupancy/issues/14). 
++ Fixed a bug that prevented prediction from working for multi-species models when `X.0` was supplied as a data frame and not a matrix. See [GitHub issue 13](https://github.com/biodiverse/spOccupancy/issues/13).
++ Fixed an error that occurred when the detection-nondetection data were specified in a specific way. See [GitHub issue 12](https://github.com/biodiverse/spOccupancy/issues/12).
 
 
 # spOccupancy 0.4.0
 
 + Major new functionality for fitting multi-season (i.e., spatio-temporal) single-species occupancy models using the functions `tPGOcc()` and `stPGOcc()`. 
-+ Fixed a bug in calculation of the detection probability values in `fitted()` functions for all spOccupancy model objects. See [this Github issue](https://github.com/doserjef/spOccupancy/issues/10) for more details. 
++ Fixed a bug in calculation of the detection probability values in `fitted()` functions for all spOccupancy model objects. See [this Github issue](https://github.com/biodiverse/spOccupancy/issues/10) for more details. 
 + Fixed an error that occurred when predicting for multi-species models and setting `ignore.RE = TRUE`.  
 + Fixed other small bugs that caused model fitting functions to break under specific circumstances.
 
@@ -119,7 +119,7 @@ spOccupancy v0.5.0 contains numerous substantial updates that provide new functi
 
 # spOccupancy 0.3.1
 
-+ Fixed two small problems with `intPGOcc()` and `spIntPGOcc()` that were accidentally introduced in v0.3.0. See [this Github issue](https://github.com/doserjef/spOccupancy/issues/8) for more details.
++ Fixed two small problems with `intPGOcc()` and `spIntPGOcc()` that were accidentally introduced in v0.3.0. See [this Github issue](https://github.com/biodiverse/spOccupancy/issues/8) for more details.
 + Adapted C/C++ code to properly handle characters strings when calling Fortran BLAS/LAPACK routines following the new requirements for R 4.2.0.  
 
 # spOccupancy 0.3.0

README.Rmd

@@ -15,7 +15,7 @@ knitr::opts_chunk$set(
 
 [![](http://cranlogs.r-pkg.org/badges/grand-total/spOccupancy?color=blue)](https://CRAN.R-project.org/package=spOccupancy)
 [![CRAN](https://www.r-pkg.org/badges/version/spOccupancy)](https://CRAN.R-project.org/package=spOccupancy)
-[![Codecov test coverage](https://codecov.io/gh/doserjef/spOccupancy/branch/main/graph/badge.svg)](https://codecov.io/gh/doserjef/spOccupancy?branch=main)
+[![Codecov test coverage](https://codecov.io/gh/biodiverse/spOccupancy/branch/main/graph/badge.svg)](https://codecov.io/gh/biodiverse/spOccupancy?branch=main)
 
 spOccupancy fits single-species, multi-species, and integrated spatial occupancy models using Markov chain Monte Carlo (MCMC). Models are fit using Pólya-Gamma data augmentation. Spatial models are fit using either Gaussian processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. The package provides functionality for data integration of multiple single-species occupancy data sets using a joint likelihood framework. For multi-species models, spOccupancy provides functions to account for residual species correlations in a joint species distribution model framework while accounting for imperfect detection. `spOccupancy` also provides functions for multi-season (i.e., spatio-temporal) single-species occupancy models. Below we give a very brief introduction to some of the package's functionality, and illustrate just one of the model fitting functions. For more information, see the resources referenced at the bottom of this page. 
 

README.md

@@ -6,7 +6,7 @@
 [![](http://cranlogs.r-pkg.org/badges/grand-total/spOccupancy?color=blue)](https://CRAN.R-project.org/package=spOccupancy)
 [![CRAN](https://www.r-pkg.org/badges/version/spOccupancy)](https://CRAN.R-project.org/package=spOccupancy)
 [![Codecov test
-coverage](https://app.codecov.io/gh/doserjef/spOccupancy/branch/main/graph/badge.svg)](https://codecov.io/gh/doserjef/spOccupancy?branch=main)
+coverage](https://codecov.io/gh/biodiverse/spOccupancy/branch/main/graph/badge.svg)](https://app.codecov.io/gh/biodiverse/spOccupancy?branch=main)
 
 spOccupancy fits single-species, multi-species, and integrated spatial
 occupancy models using Markov chain Monte Carlo (MCMC). Models are fit
@@ -152,7 +152,7 @@ summary(out)
 #> Thinning Rate: 4
 #> Number of Chains: 3
 #> Total Posterior Samples: 9000
-#> Run Time (min): 1.2816
+#> Run Time (min): 1.3642
 #> 
 #> Occurrence (logit scale): 
 #>                          Mean     SD    2.5%     50%   97.5%   Rhat  ESS
@@ -222,7 +222,7 @@ value of this CV score.
 
 ``` r
 out$k.fold.deviance
-#> [1] 1414.706
+#> [1] 1414.027
 ```
 
 ### Prediction