Package: multAbund 0.03.9002

multAbund: Model Multivariate Abundance and Occurence Using the Dirichlet Process Prior

This package provides RJMCMC samplers to make Bayesian inference for Joint Species Distribution models (JSDM) using a Dirichlet Process clustering method. The DP clustering method allows species to be grouped into functional guilds for modeling between species associations in abundance or occurence values at surveyed sites.

Authors:Devin S. Johnson

# Install 'multAbund' in R:

install.packages('multAbund', repos = c('https://dsjohnson.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/dsjohnson/multabund/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

On CRAN:

openblas cpp

2.18 score 3 stars 5 scripts 7 exports 15 dependencies

Last updated from:91880bfd44. Checks:11 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	191
linux-devel-x86_64	WARNING	229
source / vignettes	OK	256
linux-release-arm64	WARNING	195
linux-release-x86_64	WARNING	228
macos-release-arm64	WARNING	155
macos-release-x86_64	WARNING	262
macos-oldrel-arm64	WARNING	109
macos-oldrel-x86_64	WARNING	298
windows-devel	WARNING	208
windows-release	WARNING	200
windows-oldrel	WARNING	193
wasm-release	OK	207

Exports:get_opt_alpha_prior make_data_list mult_abund_norm mult_abund_pois mult_abund_probit mult_abund_zip view_example

Dependencies:ADGofTest cluster colorspace copula gsl lattice Matrix mvtnorm numDeriv pcaPP pspline Rcpp RcppArmadillo RcppProgress stabledist

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Use Dirichlet Process Prior to Model Multivariate Animal Abundance and Occurance	multAbund-package multAbund
Obtain parameters for gamma prior such that the distribution of the number of groups is equal to the 'target' argument	get_opt_alpha_prior
Make necessary data matrices for multivariate abundance and occurence RJMCMC functions	make_data_list
Perform RJMCMC for posterior sampling of multivariate cluster abundance model with Gaussian observations	mult_abund_norm
Perform RJMCMC for posterior sampling of multivariate cluster abundance model with Poisson observations	mult_abund_pois
Perform RJMCMC for posterior sampling of multivariate cluster occurence model with Bernoulli observations	mult_abund_probit
Perform RJMCMC for posterior sampling of multivariate cluster abundance model with Zero-Inflated Poisson observations	mult_abund_zip
View simulation example	view_example