Title: Bayesian Ordination and Regression AnaLysis
Description: Bayesian model-based approaches for analyzing multivariate data in ecology. Estimation is performed using Bayesian/Markov Chain Monte Carlo (MCMC) methods via JAGS. Three types of models may be fitted: 1) With explanatory variables only, boral fits independent column GLMs such that the columns of the response matrix are assumed to be independent; 2) With latent variables only, boral fits a purely latent variable model to perform 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.

Description: 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 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.

Imports: R2jags, mvtnorm, fishMod, MASS, stats, graphics, grDevices

Suggests: mvabund (>= 3.8.4), corrplot, testthat

Imports: R2jags, mvtnorm, fishMod, MASS, stats, graphics, grDevices,

Description: 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.