simulate.MCMCglmm: Simulate method for GLMMs fitted with MCMCglmm

In MCMCglmm: MCMC Generalised Linear Mixed Models

Simulate method for GLMMs fitted with MCMCglmm

Description

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(s)

Jarrod Hadfield [e-mail]

See Also

MCMCglmm

MCMCglmm documentation built on July 9, 2023, 5:24 p.m.