bootinvFIM.merMod

Compute the inverse of the Fisher Information Matrix using parametric bootstrap

An implementation of the Likelihood ratio Test (LRT) for testing that,
in a (non)linear mixed effects model, the variances of a subset of the random
effects are equal to zero. There is no restriction on the subset of variances
that can be tested: for example, it is possible to test that all the variances
are equal to zero. Note that the implemented test is asymptotic.
This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'.
Charlotte Baey and Estelle Kuhn (2019) <doi:10.18637/jss.v107.i06>.

Charlotte Baey

varTestnlme

Variance Components Testing for Linear and Nonlinear Mixed
Effects Models

Estelle Kuhn

bootinvFIM.merMod function

<dl><dt>m</dt>
<dd>the model under H1</dd>
<dt>B</dt>
<dd>the bootstrap sample size</dd>
<dt>seed</dt>
<dd>a seed for the random generator</dd></dl>

Arguments

Compute the inverse of the Fisher Information Matrix using parametric bootstrap — bootinvFIM.merMod

<dl>

<dt>m</dt>
<dd>the model under H1</dd>


<dt>B</dt>
<dd>the bootstrap sample size</dd>


<dt>seed</dt>
<dd>a seed for the random generator</dd>

</dl>

bootinvFIM.merMod: Compute the inverse of the Fisher Information Matrix using parametric bootstrap

Description

Usage

Arguments