Simulate method for GLMMs fitted with MCMCglmm

Simulated response vectors for GLMMs fitted with MCMCglmm

Usage

# S3 method for class 'MCMCglmm'
simulate(object, nsim = 1, seed = NULL, newdata=NULL, marginal = object$Random$formula, 
          type = "response", it=NULL, posterior = "all", verbose=FALSE, ...)

Arguments

object

an object of class "MCMCglmm"

nsim

number of response vectors to simulate. Defaults to 1.

seed

Either NULL or an integer that will be used in a call to set.seed before simulating the response vectors. The default, NULL will not change the random generator state.

newdata

An optional data frame for which to simulate new observations

marginal

formula defining random effects to be maginalised

type

character; either "terms" (link scale) or "response" (data scale)

it

integer; optional, MCMC iteration on which predictions should be based

posterior

character; if it is NULL should the response vector be simulated using the marginal posterior means ("mean") of the parameters, or the posterior modes ("mode"), random draws from the posterior with replacement ("distribution") or without replacement ("all")

verbose

logical; if TRUE, warnings are issued with newdata when the original model has fixed effects that do not appear in newdata and/or newdata has random effects not present in the original model.

...

Further arguments to be passed

Value

A matrix (with nsim columns) of simulated response vectors

Author

Jarrod Hadfield j.hadfield@ed.ac.uk

See also

MCMCglmm