Package: spOccupancy 0.8.0

Jeffrey Doser

spOccupancy: Single-Species, Multi-Species, and Integrated Spatial Occupancy Models

Fits single-species, multi-species, and integrated non-spatial and spatial occupancy models using Markov Chain Monte Carlo (MCMC). Models are fit using Polya-Gamma data augmentation detailed in Polson, Scott, and Windle (2013) <doi:10.1080/01621459.2013.829001>. Spatial models are fit using either Gaussian processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, Datta, and Banerjee (2022) <doi:10.18637/jss.v103.i05>. Provides functionality for data integration of multiple single-species occupancy data sets using a joint likelihood framework. Details on data integration are given in Miller, Pacifici, Sanderlin, and Reich (2019) <doi:10.1111/2041-210X.13110>. Details on single-species and multi-species models are found in MacKenzie, Nichols, Lachman, Droege, Royle, and Langtimm (2002) <doi:10.1890/0012-9658(2002)083[2248:ESORWD]2.0.CO;2> and Dorazio and Royle <doi:10.1198/016214505000000015>, respectively.

Authors:Jeffrey Doser [aut, cre], Andrew Finley [aut], Marc Kery [ctb]

spOccupancy_0.8.0.tar.gz
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spOccupancy.pdf |spOccupancy.html✨
spOccupancy/json (API)
NEWS

# Install 'spOccupancy' in R:
install.packages('spOccupancy', repos = c('https://biodiverse.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/biodiverse/spoccupancy/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • hbef2015 - Detection-nondetection data of 12 foliage gleaning bird species in 2015 in the Hubbard Brook Experimental Forest
  • hbefElev - Elevation in meters extracted at a 30m resolution across the Hubbard Brook Experimental Forest
  • hbefTrends - Detection-nondetection data of 12 foliage gleaning bird species from 2010-2018 in the Hubbard Brook Experimental Forest
  • neon2015 - Detection-nondetection data of 12 foliage gleaning bird species in 2015 in Bartlett Experimental Forest in New Hampshire, USA

On CRAN:

7.25 score 51 stars 166 scripts 993 downloads 38 exports 21 dependencies

Last updated 29 days agofrom:e251a2b585. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-win-x86_64OKOct 26 2024
R-4.5-linux-x86_64OKOct 26 2024
R-4.4-win-x86_64OKOct 26 2024
R-4.4-mac-x86_64OKOct 26 2024
R-4.4-mac-aarch64OKOct 26 2024
R-4.3-win-x86_64OKOct 26 2024
R-4.3-mac-x86_64OKOct 26 2024
R-4.3-mac-aarch64OKOct 26 2024

Exports:getSVCSamplesintMsPGOccintPGOcclfJSDMlfMsPGOccmsPGOccPGOccpostHocLMppcOccsfJSDMsfMsPGOccsimBinomsimIntMsOccsimIntOccsimMsOccsimOccsimTBinomsimTIntOccsimTMsOccsimTOccspIntPGOccspMsPGOccspPGOccstIntPGOccstMsPGOccstPGOccsvcMsPGOccsvcPGBinomsvcPGOccsvcTIntPGOccsvcTMsPGOccsvcTPGBinomsvcTPGOcctIntPGOcctMsPGOcctPGOccupdateMCMCwaicOcc

Dependencies:abindbootcodacodetoolsdigestdoParalleldoRNGforeachiteratorslatticelme4MASSMatrixminqanlmenloptrRANNRcppRcppEigenrngtoolsspAbundance

Readme and manuals

Help Manual

Help pageTopics
Single-Species, Multi-Species, and Integrated Spatial Occupancy ModelsspOccupancy-package spOccupancy
Extract Model Fitted Values for intPGOcc Objectfitted.intPGOcc
Extract Model Fitted Values for lfJSDM Objectfitted.lfJSDM
Extract Model Fitted Values for lfMsPGOcc Objectfitted.lfMsPGOcc
Extract Model Fitted Values for msPGOcc Objectfitted.msPGOcc
Extract Model Fitted Values for PGOcc Objectfitted.PGOcc
Extract Model Fitted Values for sfJSDM Objectfitted.sfJSDM
Extract Model Fitted Values for sfMsPGOcc Objectfitted.sfMsPGOcc
Extract Model Fitted Values for spIntPGOcc Objectfitted.spIntPGOcc
Extract Model Fitted Values for spMsPGOcc Objectfitted.spMsPGOcc
Extract Model Fitted Values for spPGOcc Objectfitted.spPGOcc
Extract Model Fitted Values for stIntPGOcc Objectfitted.stIntPGOcc
Extract Model Fitted Values for stMsPGOcc Objectfitted.stMsPGOcc
Extract Model Fitted Values for stPGOcc Objectfitted.stPGOcc
Extract Model Fitted Values for svcMsPGOcc Objectfitted.svcMsPGOcc
Extract Model Fitted Values for svcPGBinom Objectfitted.svcPGBinom
Extract Model Fitted Values for svcPGOcc Objectfitted.svcPGOcc
Extract Model Fitted Values for svcTIntPGOcc Objectfitted.svcTIntPGOcc
Extract Model Fitted Values for svcTMsPGOcc Objectfitted.svcTMsPGOcc
Extract Model Fitted Values for svcTPGBinom Objectfitted.svcTPGBinom
Extract Model Fitted Values for svcTPGOcc Objectfitted.svcTPGOcc
Extract Model Fitted Values for tIntPGOcc Objectfitted.tIntPGOcc
Extract Model Fitted Values for tMsPGOcc Objectfitted.tMsPGOcc
Extract Model Fitted Values for tPGOcc Objectfitted.tPGOcc
Extract spatially-varying coefficient MCMC samplesgetSVCSamples
Detection-nondetection data of 12 foliage gleaning bird species in 2015 in the Hubbard Brook Experimental Foresthbef2015
Elevation in meters extracted at a 30m resolution across the Hubbard Brook Experimental ForesthbefElev
Detection-nondetection data of 12 foliage gleaning bird species from 2010-2018 in the Hubbard Brook Experimental ForesthbefTrends
Function for Fitting Integrated Multi-Species Occupancy Models Using Polya-Gamma Latent VariablesintMsPGOcc
Function for Fitting Single-Species Integrated Occupancy Models Using Polya-Gamma Latent VariablesintPGOcc
Function for Fitting a Latent Factor Joint Species Distribution ModellfJSDM
Function for Fitting Latent Factor Multi-Species Occupancy ModelslfMsPGOcc
Function for Fitting Multi-Species Occupancy Models Using Polya-Gamma Latent VariablesmsPGOcc
Detection-nondetection data of 12 foliage gleaning bird species in 2015 in Bartlett Experimental Forest in New Hampshire, USAneon2015
Function for Fitting Single-Species Occupancy Models Using Polya-Gamma Latent VariablesPGOcc
Function for Fitting Linear Mixed Models with Previous Model EstimatespostHocLM
Function for performing posterior predictive checksppcOcc
Function for prediction at new locations for integrated multi-species occupancy modelspredict.intMsPGOcc
Function for prediction at new locations for single-species integrated occupancy modelspredict.intPGOcc
Function for prediction at new locations for latent factor joint species distribution modelspredict.lfJSDM
Function for prediction at new locations for latent factor multi-species occupancy modelspredict.lfMsPGOcc
Function for prediction at new locations for multi-species occupancy modelspredict.msPGOcc
Function for prediction at new locations for single-species occupancy modelspredict.PGOcc
Function for prediction at new locations for spatial factor joint species distribution modelpredict.sfJSDM
Function for prediction at new locations for spatial factor multi-species occupancy modelspredict.sfMsPGOcc
Function for prediction at new locations for single-species integrated spatial occupancy modelspredict.spIntPGOcc
Function for prediction at new locations for multi-species spatial occupancy modelspredict.spMsPGOcc
Function for prediction at new locations for single-species spatial occupancy modelspredict.spPGOcc
Function for prediction at new locations for multi-season single-species spatial integrated occupancy modelspredict.stIntPGOcc
Function for prediction at new locations for multi-season multi-species spatial occupancy modelspredict.stMsPGOcc
Function for prediction at new locations for multi-season single-species spatial occupancy modelspredict.stPGOcc
Function for prediction at new locations for spatially varying coefficient multi-species occupancy modelspredict.svcMsPGOcc
Function for prediction at new locations for single-species spatially-varying coefficient Binomial modelspredict.svcPGBinom
Function for prediction at new locations for single-species spatially-varying coefficient occupancy modelspredict.svcPGOcc
Function for prediction at new locations for multi-season single-species spatially-varying coefficient integrated occupancy modelspredict.svcTIntPGOcc
Function for prediction at new locations for multi-season multi-species spatially-varying coefficient occupancy modelspredict.svcTMsPGOcc
Function for prediction at new locations for multi-season single-species spatially-varying coefficient binomial modelspredict.svcTPGBinom
Function for prediction at new locations for multi-season single-species spatially-varying coefficient occupancy modelspredict.svcTPGOcc
Function for prediction at new locations for multi-season single-species integrated occupancy modelspredict.tIntPGOcc
Function for prediction at new locations for multi-season multi-species occupancy modelspredict.tMsPGOcc
Function for prediction at new locations for multi-season single-species occupancy modelspredict.tPGOcc
Occupancy and detection residuals for 'PGOcc' modelsresiduals.PGOcc
Occupancy and detection residuals for 'spPGOcc' modelsresiduals.spPGOcc
Occupancy and detection residuals for 'svcPGOcc' modelsresiduals.svcPGOcc
Function for Fitting a Spatial Factor Joint Species Distribution ModelsfJSDM
Function for Fitting Spatial Factor Multi-Species Occupancy ModelssfMsPGOcc
Simulate Single-Species Binomial DatasimBinom
Simulate Multi-Species Detection-Nondetection Data from Multiple Data SourcessimIntMsOcc
Simulate Single-Species Detection-Nondetection Data from Multiple Data SourcessimIntOcc
Simulate Multi-Species Detection-Nondetection DatasimMsOcc
Simulate Single-Species Detection-Nondetection DatasimOcc
Simulate Multi-Season Single-Species Binomial DatasimTBinom
Simulate Single-Species Multi-Season Detection-Nondetection Data from Multiple Data SourcessimTIntOcc
Simulate Multi-Species Multi-Season Detection-Nondetection DatasimTMsOcc
Simulate Multi-Season Single-Species Detection-Nondetection DatasimTOcc
Function for Fitting Single-Species Integrated Spatial Occupancy Models Using Polya-Gamma Latent VariablesspIntPGOcc
Function for Fitting Multi-Species Spatial Occupancy Models Using Polya-Gamma Latent VariablesspMsPGOcc
Function for Fitting Single-Species Spatial Occupancy Models Using Polya-Gamma Latent VariablesspPGOcc
Function for Fitting Multi-Season Single-Species Spatial Integrated Occupancy Models Using Polya-Gamma Latent VariablesstIntPGOcc
Function for Fitting Multi-Species Multi-Season Spatial Occupancy ModelsstMsPGOcc
Function for Fitting Multi-Season Single-Species Spatial Occupancy Models Using Polya-Gamma Latent VariablesstPGOcc
Methods for intMsPGOcc Objectplot.intMsPGOcc print.intMsPGOcc summary.intMsPGOcc
Methods for intPGOcc Objectplot.intPGOcc print.intPGOcc summary.intPGOcc
Methods for lfJSDM Objectplot.lfJSDM print.lfJSDM summary.lfJSDM
Methods for lfMsPGOcc Objectplot.lfMsPGOcc print.lfMsPGOcc summary.lfMsPGOcc
Methods for msPGOcc Objectplot.msPGOcc print.msPGOcc summary.msPGOcc
Methods for PGOcc Objectplot.PGOcc print.PGOcc summary.PGOcc
Methods for postHocLM Objectprint.postHocLM summary.postHocLM
Methods for ppcOcc Objectsummary.ppcOcc
Methods for sfJSDM Objectplot.sfJSDM print.sfJSDM summary.sfJSDM
Methods for sfMsPGOcc Objectplot.sfMsPGOcc print.sfMsPGOcc summary.sfMsPGOcc
Methods for spIntPGOcc Objectplot.spIntPGOcc print.spIntPGOcc summary.spIntPGOcc
Methods for spMsPGOcc Objectplot.spMsPGOcc print.spMsPGOcc summary.spMsPGOcc
Methods for spPGOcc Objectplot.spPGOcc print.spPGOcc summary.spPGOcc
Methods for stIntPGOcc Objectplot.stIntPGOcc print.stIntPGOcc summary.stIntPGOcc
Methods for stMsPGOcc Objectplot.stMsPGOcc print.stMsPGOcc summary.stMsPGOcc
Methods for stPGOcc Objectplot.stPGOcc print.stPGOcc summary.stPGOcc
Methods for svcMsPGOcc Objectplot.svcMsPGOcc print.svcMsPGOcc summary.svcMsPGOcc
Methods for svcPGBinom Objectplot.svcPGBinom print.svcPGBinom summary.svcPGBinom
Methods for svcPGOcc Objectplot.svcPGOcc print.svcPGOcc summary.svcPGOcc
Methods for svcTIntPGOcc Objectplot.svcTIntPGOcc print.svcTIntPGOcc summary.svcTIntPGOcc
Methods for svcTMsPGOcc Objectplot.svcTMsPGOcc print.svcTMsPGOcc summary.svcTMsPGOcc
Methods for svcTPGBinom Objectplot.svcTPGBinom print.svcTPGBinom summary.svcTPGBinom
Methods for svcTPGOcc Objectplot.svcTPGOcc print.svcTPGOcc summary.svcTPGOcc
Methods for tIntPGOcc Objectplot.tIntPGOcc print.tIntPGOcc summary.tIntPGOcc
Methods for tMsPGOcc Objectplot.tMsPGOcc print.tMsPGOcc summary.tMsPGOcc
Methods for tPGOcc Objectplot.tPGOcc print.tPGOcc summary.tPGOcc
Function for Fitting Multi-Species Spatially-Varying Coefficient Occupancy ModelssvcMsPGOcc
Function for Fitting Single-Species Spatially-Varying Coefficient Binomial Models Using Polya-Gamma Latent VariablessvcPGBinom
Function for Fitting Single-Species Spatially-Varying Coefficient Occupancy Models Using Polya-Gamma Latent VariablessvcPGOcc
Function for Fitting Multi-Season Single-Species Spatially-varying Coefficient Integrated Occupancy Models Using Polya-Gamma Latent VariablessvcTIntPGOcc
Function for Fitting Multi-Species Multi-Season Spatially-Varying Coefficient Occupancy ModelssvcTMsPGOcc
Function for Fitting Multi-Season Single-Species Spatially-Varying Coefficient Binomial Models Using Polya-Gamma Latent VariablessvcTPGBinom
Function for Fitting Multi-Season Single-Species Spatially-Varying Coefficient Occupancy Models Using Polya-Gamma Latent VariablessvcTPGOcc
Function for Fitting Multi-Season Single-Species Integrated Occupancy Models Using Polya-Gamma Latent VariablestIntPGOcc
Function for Fitting Multi-Species Multi-Season Occupancy ModelstMsPGOcc
Function for Fitting Multi-Season Single-Species Occupancy Models Using Polya-Gamma Latent VariablestPGOcc
Update a spOccupancy or spAbundance model run with more MCMC iterationsupdateMCMC
Compute Widely Applicable Information Criterion for spOccupancy Model ObjectswaicOcc