Function reference • spAbundance

N-mixture Models

NMix(): Function for Fitting Single-Species N-mixture Models

spNMix(): Function for Fitting Single-Species Spatial N-Mixture Models

msNMix(): Function for Fitting Multi-species N-mixture Models

lfMsNMix(): Function for Fitting Latent Factor Multi-species N-mixture Models

sfMsNMix(): Function for Fitting Spatial Factor Multi-species N-mixture Models

Hierarchical Distance Sampling Models

DS(): Function for Fitting Single-Species Hierarchical Distance Sampling Models

spDS(): Function for Fitting Single-Species Spatially-Explicit Hierarchical Distance Sampling Models

msDS(): Function for Fitting Multi-Species Hierarchical Distance Sampling Models

lfMsDS(): Function for Fitting Latent Factor Multi-Species Hierarchical Distance Sampling Models

sfMsDS(): Function for Fitting Spatial Factor Multi-Species Hierarchical Distance Sampling Models

Generalized Linear Mixed Models

abund(): Function for Fitting Univariate Abundance GLMMs

spAbund(): Function for Fitting Univariate Spatial Abundance GLMs

svcAbund(): Function for Fitting Univariate Spatialy-Varying Coefficient GLMMs

msAbund(): Function for Fitting Multivariate Abundance GLMMs

lfMsAbund(): Function for Fitting Latent Factor Multivariate Abundance GLMMs

sfMsAbund(): Function for Fitting Spatial Factor Multivariate Abundance GLMMs

svcMsAbund(): Function for Fitting Spatially-Varying Coefficient Multivariate Abundance GLMMs

Goodness of Fit and Model Assessment

ppcAbund(): Function for performing posterior predictive checks

waicAbund(): Compute Widely Applicable Information Criterion for spAbundance Model Objects

Data Simulation

simNMix(): Simulate Single-Species Count Data with Imperfect Detection

simMsNMix(): Simulate Multi-Species Repeated Count Data with Imperfect Detection

simDS(): Simulate Single-Species Distance Sampling Data

simMsDS(): Simulate Multi-Species Distance Sampling Data

simAbund(): Simulate Univariate Data for Testing GLMMs

simMsAbund(): Simulate Multivariate Data for Testing GLMMs

Summary

summary(<NMix>) print(<NMix>) plot(<NMix>): Methods for NMix Object

summary(<spNMix>) print(<spNMix>) plot(<spNMix>): Methods for spNMix Object

summary(<msNMix>) print(<msNMix>) plot(<msNMix>): Methods for msNMix Object

summary(<lfMsNMix>) print(<lfMsNMix>) plot(<lfMsNMix>): Methods for lfMsNMix Object

summary(<sfMsNMix>) print(<sfMsNMix>) plot(<sfMsNMix>): Methods for sfMsNMix Object

summary(<DS>) print(<DS>) plot(<DS>): Methods for DS Object

summary(<spDS>) print(<spDS>) plot(<spDS>): Methods for spDS Object

summary(<msDS>) print(<msDS>) plot(<msDS>): Methods for msDS Object

summary(<lfMsDS>) print(<lfMsDS>) plot(<lfMsDS>): Methods for lfMsDS Object

summary(<sfMsDS>) print(<sfMsDS>) plot(<sfMsDS>): Methods for sfMsDS Object

summary(<abund>) print(<abund>) plot(<abund>): Methods for abund Object

summary(<spAbund>) print(<spAbund>) plot(<spAbund>): Methods for spAbund Object

summary(<svcAbund>) print(<svcAbund>) plot(<svcAbund>): Methods for svcAbund Object

summary(<msAbund>) print(<msAbund>) plot(<msAbund>): Methods for msAbund Object

summary(<lfMsAbund>) print(<lfMsAbund>) plot(<lfMsAbund>): Methods for lfMsAbund Object

summary(<sfMsAbund>) print(<sfMsAbund>) plot(<sfMsAbund>): Methods for sfMsAbund Object

summary(<svcMsAbund>) print(<svcMsAbund>) plot(<svcMsAbund>): Methods for svcMsAbund Object

Prediction

predict(<NMix>): Function for prediction at new locations for single-species N-mixture models

predict(<spNMix>): Function for prediction at new locations for single-species spatial N-mixture models

predict(<msNMix>): Function for prediction at new locations for multi-species N-mixture models

predict(<lfMsNMix>): Function for prediction at new locations for latent factor multi-species N-mixture models

predict(<sfMsNMix>): Function for prediction at new locations for spatial factor multi-species N-mixture models

predict(<DS>): Function for prediction at new locations for single-species hierarchical distance sampling models

predict(<spDS>): Function for prediction at new locations for single-species spatially-explicit hierarchical distance sampling models

predict(<msDS>): Function for prediction at new locations for multi-species hierarchical distance sampling models

predict(<lfMsDS>): Function for prediction at new locations for latent factor multi-species hierarchical distance sampling models

predict(<sfMsDS>): Function for prediction at new locations for spatial factor multi-species hierarchical distance sampling models

predict(<abund>): Function for prediction at new locations for univariate GLMMs

predict(<spAbund>): Function for prediction at new locations for univariate spatial GLMMs

predict(<svcAbund>): Function for prediction at new locations for univariate Gaussian spatially-varying coefficient models

predict(<msAbund>): Function for prediction at new locations for multivariate GLMMs

predict(<lfMsAbund>): Function for prediction at new locations for latent factor multivariate GLMMs

predict(<sfMsAbund>): Function for prediction at new locations for spatial factor multivariate GLMMs

predict(<svcMsAbund>): Function for prediction at new locations for multivariate spatially-varying coefficient GLMMs

Fitted Values

fitted(<NMix>): Extract Model Fitted Values for NMix Object

fitted(<spNMix>): Extract Model Fitted Values for spNMix Object

fitted(<msNMix>): Extract Model Fitted Values for msNMix Object

fitted(<lfMsNMix>): Extract Model Fitted Values for lfMsNMix Object

fitted(<sfMsNMix>): Extract Model Fitted Values for sfMsNMix Object

fitted(<DS>): Extract Model Fitted Values for DS Object

fitted(<spDS>): Extract Model Fitted Values for spDS Object

fitted(<msDS>): Extract Model Fitted Values for msDS Object

fitted(<lfMsDS>): Extract Model Fitted Values for lfMsDS Object

fitted(<sfMsDS>): Extract Model Fitted Values for sfMsDS Object

fitted(<abund>): Extract Model Fitted Values for abund Object

fitted(<spAbund>): Extract Model Fitted Values for spAbund Object

fitted(<svcAbund>): Extract Model Fitted Values for svcAbund Object

fitted(<msAbund>): Extract Model Fitted Values for msAbund Object

fitted(<lfMsAbund>): Extract Model Fitted Values for lfMsAbund Object

fitted(<sfMsAbund>): Extract Model Fitted Values for sfMsAbund Object

fitted(<svcMsAbund>): Extract Model Fitted Values for svcMsAbund Object

Data

dataNMixSim: Simulated repeated count data of 6 species across 225 sites

hbefCount2015: Count data of 12 foliage gleaning bird species in 2015 in the Hubbard Brook Experimental Forest

neonDWP: Distance sampling data of 16 bird species observed in the Disney Wilderness Preserve in 2018 in Florida, USA

neonPredData: Land cover covariates and coordinates at a 1ha resolution across Disney Wilderness Preserve

bbsData: Count data for six warbler species in Pennsylvania, USA

bbsPredData: Covariates and coordinates for prediction of relative warbler abundance in Pennsylvania, USA