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, ...)
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
posterior mean, 95% HPD interval, MCMC p-values and effective sample size of scaling parameter in theta_scale models.
an object of class "MCMCglmm"
logical: should the random effects be summarised
Further arguments to be passed
Jarrod Hadfield j.hadfield@ed.ac.uk
MCMCglmm