WILL BE ADDED.
GLMM_longitDA2(mod, w.prior, y, id, x, z, xz.common = TRUE,
keep.comp.prob = FALSE, level = 0.95,
info, silent = FALSE)A list with the following components:
ADD DESCRIPTION
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.
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.
see xz.common below.
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 z of GLMM_MCMC
function.
If FALSE then X and Z matrices for the GLMM may differ across
clusters. In that case, arguments x and z are both
lists of length equal to the number of clusters and each component
of lists x and z has the same structure as arguments
x and z of GLMM_MCMC function.
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 of HPD credible intervals that are calculated for
the component probabilities if keep.comp.prob is TRUE.
interval in which the function prints the progress of
computation (unless silent is TRUE).
logical value indicating whether to switch-off printing the information during calculations.
Arnošt Komárek arnost.komarek@mff.cuni.cz
This function complements a paper being currently in preparation.
GLMM_longitDA2 differs in many aspects from GLMM_longitDA2!
GLMM_MCMC, GLMM_longitDA.