boral: Bayesian Ordination and Regression AnaLysis

Bayesian approaches for analyzing multivariate data in ecology. Estimation is performed using Markov Chain Monte Carlo (MCMC) methods via Three. JAGS types of models may be fitted: 1) With explanatory variables only, boral fits independent column Generalized Linear Models (GLMs) to each column of the response matrix; 2) With latent variables only, boral fits a purely latent variable model for model-based unconstrained ordination; 3) With explanatory and latent variables, boral fits correlated column GLMs with latent variables to account for any residual correlation between the columns of the response matrix.

Version:	2.0.2
Depends:	coda
Imports:	abind, corpcor, fishMod, graphics, grDevices, lifecycle, MASS, mvtnorm, R2jags, reshape2, stats
Suggests:	mvabund (≥ 4.0.1), corrplot
Published:	2024-03-24
DOI:	10.32614/CRAN.package.boral
Author:	Francis K.C. Hui [aut, cre], Wade Blanchard [aut]
Maintainer:	Francis K.C. Hui <fhui28 at gmail.com>
License:	GPL-2
NeedsCompilation:	no
Citation:	boral citation info
In views:	Environmetrics
CRAN checks:	boral results

Documentation:

Reference manual:

boral.pdf

Downloads:

Package source:	boral_2.0.2.tar.gz
Windows binaries:	r-devel: boral_2.0.2.zip, r-release: boral_2.0.2.zip, r-oldrel: boral_2.0.2.zip
macOS binaries:	r-release (arm64): boral_2.0.2.tgz, r-oldrel (arm64): boral_2.0.2.tgz, r-release (x86_64): boral_2.0.2.tgz, r-oldrel (x86_64): boral_2.0.2.tgz
Old sources:	boral archive

Reverse dependencies:

Reverse suggests:

jSDM

Linking:

Please use the canonical form https://CRAN.R-project.org/package=boral to link to this page.