# buildV

##### Forms expected (co)variances for GLMMs fitted with MCMCglmm

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

- Keywords
- models

##### 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).

##### See Also

*Documentation reproduced from package MCMCglmm, version 2.29, License: GPL (>= 2)*