| 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 |
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 |
theta_scale |
posterior mean, 95% HPD interval, MCMC p-values and effective sample size of scaling parameter in theta_scale models. |
Author(s)
Jarrod Hadfield j.hadfield@ed.ac.uk