MCMCglmm: summary.MCMCglmm – R documentation

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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.

## S3 method for class 'MCMCglmm'
summary(object, random=FALSE, ...)

`object`	an object of class `"MCMCglmm"`
`random`	logical: should the random effects be summarised
`...`	Further arguments to be passed

`DIC`	Deviance Information Criterion
`fixed.formula`	model formula for the fixed terms
`random.formula`	model formula for the random terms
`residual.formula`	model formula for the residual terms
`solutions`	posterior mean, 95% HPD interval, MCMC p-values and effective sample size of fixed (and random) effects
`Gcovariances`	posterior mean, 95% HPD interval and effective sample size of random effect (co)variance components
`Gterms`	indexes random effect (co)variances by the component terms defined in the random formula
`Rcovariances`	posterior mean, 95% HPD interval and effective sample size of residual (co)variance components
`Rterms`	indexes residuals (co)variances by the component terms defined in the rcov formula
`csats`	chain length, burn-in and thinning interval
`cutpoints`	posterior mean, 95% HPD interval and effective sample size of cut-points from an ordinal model