# simulate.MCMCglmm

##### Simulate method for GLMMs fitted with MCMCglmm

Simulated response vectors for GLMMs fitted with MCMCglmm

- Keywords
- models

##### Usage

```
# S3 method for 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

##### See Also

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