gfam

This function is inspired by a function of the same name in the <code>mgcv</code>
package woodGeneralizedAdditiveModels2017galamm, and supports
setting up mixed response type models. When using this function, the response
variable must be supported as a two-column matrix, in which the first column
contains the response and the second column contains an index mapping the
response to the list elements provided in the argument <code>fl</code> to this function.

Estimates generalized additive latent and
mixed models using maximum marginal likelihood,
as defined in Sorensen et al. (2023)
<doi:10.1007/s11336-023-09910-z>, which is an extension of Rabe-Hesketh and
Skrondal (2004)'s unifying framework for multilevel latent variable
modeling <doi:10.1007/BF02295939>. Efficient computation is done using sparse
matrix methods, Laplace approximation, and automatic differentiation. The
framework includes generalized multilevel models with heteroscedastic
residuals, mixed response types, factor loadings, smoothing splines,
crossed random effects, and combinations thereof. Syntax for model
formulation is close to 'lme4' (Bates et al. (2015)
<doi:10.18637/jss.v067.i01>) and 'PLmixed' (Rockwood and Jeon (2019)
<doi:10.1080/00273171.2018.1516541>).

Oystein Sorensen

galamm

Generalized Additive Latent and Mixed Models

Øystein Sørensen

Douglas Bates

Ben Bolker

Martin Maechler

Allan Leal

Fabian Scheipl

Steven Walker

Simon Wood

gfam function

<dl><dt>fl</dt>
<dd>A list of families. Currently <code>gaussian</code>, <code>binomial</code>, and
<code>poisson</code> with canonical link functions are supported.</dd></dl>

Arguments

Grouped families — gfam

<dl>

<dt>fl</dt>
<dd>A list of families. Currently <code>gaussian</code>, <code>binomial</code>, and
<code>poisson</code> with canonical link functions are supported.</dd>

</dl>

Grouped families

gfam: Grouped families

Description

Usage

Value

Arguments

References

See Also