GLMM_longitDA2: Discriminant analysis for longitudinal profiles based on fitted GLMM's

Description

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Usage

GLMM_longitDA2(mod, w.prior, y, id, x, z, xz.common = TRUE,
               keep.comp.prob = FALSE, level = 0.95,
               info, silent = FALSE)

Arguments

mod

a list containing models fitted with the GLMM_MCMC function. Each component of the list is the GLMM fitted in the training dataset of each cluster.

w.prior

a vector with prior cluster weights. The length of this argument must be the same as the length of argument mod. Can also be given relatively, e.g., as c(1, 1) which means that both prior weights are equal to 1/2.

vector, matrix or data frame (see argument y of GLMM_MCMC function) with responses of objects that are to be clustered.

vector which determines clustered observations (see also argument y of GLMM_MCMC function).

see xz.common below.

xz.common

a logical value.

If TRUE then it is assumed that the X and Z matrices are the same for GLMM in each cluster. In that case, arguments x and z have the same structure as arguments x and

keep.comp.prob

a logical value indicating whether the allocation probabilities should be kept for all MCMC iterations. This may ask for quite some memory but it is necessary if credible intervals etc. should be calculated for the component probabilities.

level

level of HPD credible intervals that are calculated for the component probabilities if keep.comp.prob is TRUE.

info

interval in which the function prints the progress of computation (unless silent is TRUE).

silent

logical value indicating whether to switch-off printing the information during calculations.

Value

A list with the following components:
ADDADD DESCRIPTION

Details

This function complements a paper being currently in preparation.

GLMM_longitDA2 differs in many aspects from GLMM_longitDA2!

Examples

Run this code

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