An object of class inla, ie a result of a call to inla().

If given, the groups are taken from this argument. group.cv must be the output of previous call to inla.group.cv().

Number of level.sets to use. The default value -1 corresponds to leave-one-out cross-validation.

One of "posterior" or "prior". See the vignette for details.

The maximum size of a group. If the computed group-size is larger, it will be truncated to size.max.

An (optional) predefined list of groups. See the vignette for details.

An optional list of data-indices to use. If not given, then all data are used.

An optional list of lists of indices to use a friends

Run with verbose output of some of the internals in the calculations. This option will also enable inla(..., verbose=TRUE) if its not enabled already.

Two correlations with a difference less than epsilon, will be classified as identical.

When strategy="prior", prior.diagonal is added to the diagonal of the prior precision matrix to avoid singularities

For strategy="prior", then this gives a vector of the name of model-components TO USE when computing the groups. See the vignette for details. Not both of keep and remove can be defined.

For strategy="prior", then this gives a vector of the name of model-components NOT TO USE when computing the groups. See the vignette for details. Not both of keep and remove can be defined.

For strategy="prior", this is the default option which is in effect if both keep and remove are NULL. If TRUE, it will remove (or condition on) all fixed effects when computing the groups. See the vignette for details.