summary method for class "MCMCglmm". The returned object is suitable for printing with the print.summary.MCMCglmm method.
# S3 method for MCMCglmm
summary(object, random=FALSE, …)an object of class "MCMCglmm"
logical: should the random effects be summarised
Further arguments to be passed
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