Single-Species, Multi-Species, and Integrated Spatial Occupancy Models
spOccupancy-package.RdFits 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).
Spatial models are fit using either Gaussian processes or Nearest Neighbor
Gaussian Processes (NNGP) for large spatial datasets. Details on NNGPs are
given in Datta, Banerjee, Finley, and Gelfand (2016). Provides functionality
for data integration of multiple occupancy data sets using a
joint likelihood framework. Details on data integration are given in
Miller, Pacifici, Sanderlin, and Reich (2019). Details on single-species and
multi-species models are found in MacKenzie et al. (2002) and Dorazio and Royle (2005),
respectively. Details on the package functionality is given in Doser et al. (2022),
Doser, Finley, Banerjee (2023), Doser et al. (2024a,b).
See citation('spOccupancy') for how to cite spOccupancy in publications.
Single-species models
PGOcc fits single-species occupancy models.
spPGOcc fits single-species spatial occupancy models.
intPGOcc fits single-species integrated occupancy models (i.e., an occupancy model with multiple data sources).
spIntPGOcc fits single-species integrated spatial occupancy models.
tPGOcc fits a multi-season single-species occupancy model.
stPGOcc fits a multi-season single-species spatial occupancy model.
svcPGBinom fits a single-species spatially-varying coefficient GLM.
svcPGOcc fits a single-species spatially-varying coefficient occupancy model.
svcTPGBinom fits a single-species spatially-varying coefficient multi-season GLM.
svcTPGOcc fits a single-species spatially-varying coefficient multi-season occupancy model.
Multi-species models
msPGOcc fits multi-species occupancy models.
spMsPGOcc fits multi-species spatial occupancy models.
lfJSDM fits a joint species distribution model without imperfect detection.
sfJSDM fits a spatial joint species distribution model without imperfect detection.
lfMsPGOcc fits a joint species distribution model with imperfect detection (i.e., a multi-species occupancy model with residual species correlations).
sfMsPGOcc fits a spatial joint species distribution model with imperfect detection.
svcMsPGOcc fits a multi-species spatially-varying coefficient occupancy model.
tMsPGOcc fits a multi-season multi-species occupancy model.
stMsPGOcc fits a multi-season multi-species spatial occupancy model.
svcTMsPGOcc fits a multi-season multi-species spatially-varying coefficient occupancy model.
Goodness of Fit and Model Assessment Functions
ppcOcc performs posterior predictive checks.
waicOcc computes the Widely Applicable Information Criterion for spOccupancy model objects.
Data Simulation Functions
simOcc simulates single-species occupancy data.
simTOcc simulates single-species multi-season occupancy data.
simBinom simulates detection-nondetection data with perfect detection.
simTBinom simulates multi-season detection-nondetection data with perfect detection.
simMsOcc simulates multi-species occupancy data.
simIntOcc simulates single-species occupancy data from multiple data sources.
simTMsOcc simulates multi-species multi-season occupancy data from multiple data sources.
Miscellaneous
postHocLM fits post-hoc linear (mixed) models.
getSVCSamples extracts spatially varying coefficient MCMC samples.
updateMCMC updates a spOccupancy or spAbundance model object with more MCMC iterations.
All objects from model-fitting functions have support with the summary function for
displaying a concise summary of model results, the fitted function for extracting
model fitted values, and the predict function for predicting occupancy and/or detection
across an area of interest.
References
Doser, J. W., Finley, A. O., Kery, M., & Zipkin, E. F. (2022). spOccupancy: An R package for single-species, multi-species, and integrated spatial occupancy models. Methods in Ecology and Evolution, 13, 1670-1678. doi:10.1111/2041-210X.13897 .
Doser, J. W., Finley, A. O., & Banerjee, S. (2023). Joint species distribution models with imperfect detection for high-dimensional spatial data. Ecology, 104(9), e4137. doi:10.1002/ecy.4137 .
Doser, J. W., Finley, A. O., Saunders, S. P., Kery, M., Weed, A. S., & Zipkin, E. F. (2024A). Modeling complex species-environment relationships through spatially-varying coefficient occupancy models. Journal of Agricultural, Biological and Environmental Statistics. doi:10.1007/s13253-023-00595-6 .
Doser, J. W., Kery, M., Saunders, S. P., Finley, A. O., Bateman, B. L., Grand, J., Reault, S., Weed, A. S., & Zipkin, E. F. (2024B). Guidelines for the use of spatially varying coefficients in species distribution models. Global Ecology and Biogeography, 33, e13814. doi:10.1111/geb.13814 .