summary.MCMCglmm
Summarising GLMM Fits from MCMCglmm
summary method for class "MCMCglmm". The returned object is suitable for printing with the print.summary.MCMCglmm method.
- Keywords
- models
Usage
# S3 method for MCMCglmm
summary(object, random=FALSE, …)Arguments
- object
an object of class
"MCMCglmm"- random
logical: should the random effects be summarised
- …
Further arguments to be passed
Value
Deviance Information Criterion
model formula for the fixed terms
model formula for the random terms
model formula for the residual terms
posterior mean, 95% HPD interval, MCMC p-values and effective sample size of fixed (and random) effects
posterior mean, 95% HPD interval and effective sample size of random effect (co)variance components
indexes random effect (co)variances by the component terms defined in the random formula
posterior mean, 95% HPD interval and effective sample size of residual (co)variance components
indexes residuals (co)variances by the component terms defined in the rcov formula
chain length, burn-in and thinning interval
posterior mean, 95% HPD interval and effective sample size of cut-points from an ordinal model