simulate.lme {nlme} | R Documentation

## Simulate Results from `lme` Models

### Description

The model `object` is fit to the data. Using the fitted values of the parameters, `nsim` new data vectors from this model are simulated. Both `object` and `m2` are fit by maximum likelihood (ML) and/or by restricted maximum likelihood (REML) to each of the simulated data vectors.

### Usage

    ## S3 method for class 'lme'
    simulate(object, nsim = 1, seed = , m2,
             method = c("REML", "ML"), niterEM = c(40, 200), useGen, ...)

### Arguments

`object` | an object inheriting from class `"lme"`, representing a fitted linear mixed-effects model, or a list containing an `lme` model specification. If given as a list, it should contain components `fixed`, `data`, and `random` with values suitable for a call to `lme`. This argument defines the null model.
`m2` | an `"lme"` object or a list, like `object` containing a second lme model specification. This argument defines the alternative model. If given as a list, only those parts of the specification that change between model `object` and `m2` need to be specified.
`seed` | an optional integer that is passed to `set.seed`. Defaults to a random integer.
`method` | an optional character array. If it includes `"REML"` the models are fit by maximizing the restricted log-likelihood. If it includes `"ML"` the log-likelihood is maximized. Defaults to `c("REML", "ML")`, in which case both methods are used.
`nsim` | an optional positive integer specifying the number of simulations to perform. Defaults to `1`. This has changed. Previously the default was 1000.
`niterEM` | an optional integer vector of length 2 giving the number of iterations of the EM algorithm to apply when fitting the `object` and `m2` to each simulated set of data. Defaults to `c(40,200)`.

`useGen`

an optional logical value. If `TRUE`, numerical derivatives are used to obtain the gradient and the Hessian of the log-likelihood in the optimization algorithm in the `ms` function. If `FALSE`, the default algorithm in `ms` for functions that do not incorporate gradient and Hessian attributes is used. Default depends on the `"pdMat"` classes used in `object` and `m2`: if both are standard classes (see `pdClasses`) then defaults to `TRUE`, otherwise defaults to `FALSE`.

`...` | optional additional arguments. None are used.

### Value

an object of class `simulate.lme` with components `null` and `alt`. Each of these has components `ML` and/or `REML` which are matrices. An attribute called `Random.seed` contains the seed that was used for the random number generator.

### Author(s)

José Pinheiro and Douglas Bates bates@stat.wisc.edu

### References

Pinheiro, J.C., and Bates, D.M. (2000) Mixed-Effects Models in S and S-PLUS, Springer.

### See Also

`lme`, `set.seed`

### Examples

    orthSim <-
       simulate.lme(list(fixed = distance ~ age, data = Orthodont,
                         random = ~ 1 | Subject), nsim = 200,
                    m2 = list(random = ~ age | Subject))

[Package nlme version 3.1-139 Index]