MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package

Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form. Markov chain Monte Carlo methods solve this problem by sampling from a series of simpler conditional distributions that can be evaluated. The R package MCMCglmm implements such an algorithm for a range of model fitting problems. More than one response variable can be analyzed simultaneously, and these variables are allowed to follow Gaussian, Poisson, multi(bi)nominal, exponential, zero-inflated and censored distributions. A range of variance structures are permitted for the random effects, including interactions with…

• SR
  Sight Research UK

  Award: NE/F015275/1
• NE
  Natural Environment Research Council

  Award: NE/F015275/1