Bayesian approaches for analyzing multivariate data in ecology. Estimation is performed using Markov Chain Monte Carlo (MCMC) methods via JAGS. Three 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: | 1.4 |
| Depends: | coda |
| Imports: | R2jags, mvtnorm, fishMod, MASS, stats, graphics, grDevices, abind |
| Suggests: | mvabund (≥ 3.8.4), corrplot |
| Published: | 2017-09-25 |
| Author: | Francis K.C. Hui |
| Maintainer: | Francis Hui <fhui28 at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | boral citation info |
| Materials: | NEWS |
| CRAN checks: | boral results |
| Reference manual: | boral.pdf |
| Package source: | boral_1.4.tar.gz |
| Windows binaries: | r-devel: boral_1.4.zip, r-release: boral_1.4.zip, r-oldrel: boral_1.4.zip |
| OS X El Capitan binaries: | r-release: boral_1.4.tgz |
| OS X Mavericks binaries: | r-oldrel: boral_1.4.tgz |
| Old sources: | boral archive |
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