nlme: simulate.lme – R documentation

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simulate.lme

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.

Examples

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

nlme

Linear and Nonlinear Mixed Effects Models

v3.1-152

GPL (>= 2) | file LICENCE

Authors

José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), Johannes Ranke [ctb] (varConstProp()), R-core [aut, cre]

Initial release

2021-02-03