buildV {MCMCglmm}

Forms expected (co)variances for GLMMs fitted with MCMCglmm

Description

Forms the expected covariance structure of link-scale observations for GLMMs fitted with MCMCglmm

Usage

buildV(object, marginal=object$Random$formula, diag=TRUE, it=NULL, posterior="mean", ...)

Arguments

object

an object of class "MCMCglmm"

marginal

formula defining random effects to be maginalised

diag

logical; if TRUE the covariances betwween observations are not calculated

it

integer; optional, MCMC iteration on which covariance structure should be based

posterior

character; if it is NULL should the covariance structure be based on the marginal posterior means ('mean') of the VCV parameters, or the posterior modes ('mode'), or a random draw from the posterior with replacement ('distribution'). If posterior=="all" the posterior distribution of observation variances is returned

...

Further arguments to be passed

Value

If diag=TRUE an n by n covariance matrix. If diag=FALSE and posterior!="all" an 1 by n matrix of variances. If posterior=="all" an nit by n matrix of variances (where nit is the number of saved MCMC iterations).

Author(s)

Jarrod Hadfield [e-mail]

See Also

MCMCglmm