R: Summarising GLMM Fits from MCMCglmm

summary.MCMCglmm {MCMCglmm} | R Documentation

## Summarising GLMM Fits from MCMCglmm

### Description

`summary` method for class `"MCMCglmm"`. The returned object is suitable for printing with the `print.summary.MCMCglmm` method.

### Usage

    ## S3 method for class '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

`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

### Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

### See Also

`MCMCglmm`

[Package MCMCglmm version 2.32 Index]