G_generate

The function `G_estimate` uses a MoM method,
and `G_estimate_randint` is a special case of `G_estimate`.

Implementation of the fast univariate inference approach (Cui et al. (2022) <doi:10.1080/10618600.2021.1950006>, Loewinger et al. (2023) <doi:10.1101/2023.11.06.565896>) for fitting functional mixed models.

Erjia Cui

fastFMM

Fast Functional Mixed Models using Fast Univariate Inference

Gabriel Loewinger

Al Xin

G_generate function

<dl><dt>data</dt>
<dd>Data frame that contains the predictors and outcome</dd>
<dt>Z_lst</dt>
<dd>Transposed list of Z matrices from the univariate fits</dd>
<dt>RE_table</dt>
<dd>Table of random effects and interactions, generated from the
`lmerMod` object</dd>
<dt>MoM</dt>
<dd>Integer to determine type of MoM estimation.</dd>
<dt>ID</dt>
<dd>Name of the ID factor, assuming names of `HHat` are generated from
the same table in the same order</dd></dl>

Arguments

Creates the design matrix that allows for estimation of G — G_generate

<dl>

<dt>data</dt>
<dd>Data frame that contains the predictors and outcome</dd>


<dt>Z_lst</dt>
<dd>Transposed list of Z matrices from the univariate fits</dd>


<dt>RE_table</dt>
<dd>Table of random effects and interactions, generated from the
`lmerMod` object</dd>


<dt>MoM</dt>
<dd>Integer to determine type of MoM estimation.</dd>


<dt>ID</dt>
<dd>Name of the ID factor, assuming names of `HHat` are generated from
the same table in the same order</dd>

</dl>

G_generate: Creates the design matrix that allows for estimation of G

Description

Usage

Value

Arguments

Details