mixAK: fitted.GLMMMCMC – R documentation

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fitted.GLMMMCMC

Fitted profiles in the GLMM model

Description

It calculates fitted profiles in the (multivariate) GLMM with a normal mixture in the random effects distribution based on selected posterior summary statistic of the model parameters.

Usage

## S3 method for class 'GLMM_MCMC'
fitted(object, x, z,
  statistic=c("median", "mean", "Q1", "Q3", "2.5%", "97.5%"),
  overall=FALSE, glmer=TRUE, nAGQ=100, ...)

Arguments

`object`	object of class `GLMM_MCMC`.
`x`	matrix or list of matrices (in the case of multiple responses) for “fixed effects” part of the model used in the calculation of fitted values.
`z`	matrix or list of matrices (in the case of multiple responses) for “random effects” part of the model used in the calculation of fitted values.
`statistic`	character which specifies the posterior summary statistic to be used to calculate fitted profiles. Default is the posterior median. It applies only to the overall fit.
`overall`	logical. If `TRUE`, fitted profiles based on posterior mean/median/Q1/Q3/2.5%/97.5% of the model parameters are computed. If `FALSE`, fitted profiles based on posterior means given mixture component are calculated. Note that this depends on used re-labelling of the mixture components and hence might be misleading if re-labelling is not succesfull!
`glmer`	a logical value. If `TRUE`, the real marginal means are calculated using Gaussian quadrature.
`nAGQ`	number of quadrature points used when `glmer` is `TRUE`.
`...`	possibly extra arguments. Nothing useful at this moment.

Value

A list (one component for each of multivariate responses from the model) with fitted values calculated using the x and z matrices. If overall is FALSE, these are then matrices with one column for each mixture component.

Author(s)

Arnošt Komárek arnost.komarek[AT]mff.cuni.cz

Examples

### WILL BE ADDED.

mixAK

Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering

v5.3

GPL (>= 3)

Authors

Arnošt Komárek <arnost.komarek@mff.cuni.cz>

Initial release

2020-06-02