GLMM_MCMCprior.eps

see argument<code>prior.eps</code> of
 <code><a rd-options="" href="/link/GLMM_MCMC?package=mixAK&version=5.4" data-mini-rdoc="mixAK::GLMM_MCMC">GLMM_MCMC</a></code> function

prior.eps

see output element <code>Rc</code> of <code><a rd-options="" href="/link/GLMM_MCMCdata?package=mixAK&version=5.4" data-mini-rdoc="mixAK::GLMM_MCMCdata">GLMM_MCMCdata</a></code>
 function

see output element <code>isigma</code> of <code><a rd-options="" href="/link/GLMM_MCMCifit?package=mixAK&version=5.4" data-mini-rdoc="mixAK::GLMM_MCMCifit">GLMM_MCMCifit</a></code>
 function. It is used to determine a default value of <code>prior.eps$h</code>.
 Defaults to a vector of ones if missing

isigma

see output element <code>is.sigma</code> of <code><a rd-options="" href="/link/GLMM_MCMCifit?package=mixAK&version=5.4" data-mini-rdoc="mixAK::GLMM_MCMCifit">GLMM_MCMCifit</a></code>
 function

is.sigma

This is a help function for <code>GLMM_MCMC</code> function. 
THIS FUNCTION IS NOT TO BE CALLED BY ORDINARY USERS.

internal

Contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models.

Arnošt Komárek

mixAK

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

GLMM_MCMCprior.eps function

<dl> <dt>prior.eps</dt>
<dd>see argument<code>prior.eps</code> of
 <code>GLMM_MCMC</code> function</dd> <dt>Rc</dt>
<dd>see output element <code>Rc</code> of <code>GLMM_MCMCdata</code>
 function</dd> <dt>isigma</dt>
<dd>see output element <code>isigma</code> of <code>GLMM_MCMCifit</code>
 function. It is used to determine a default value of <code>prior.eps$h</code>.
 Defaults to a vector of ones if missing</dd> <dt>is.sigma</dt>
<dd>see output element <code>is.sigma</code> of <code>GLMM_MCMCifit</code>
 function</dd>
 
</dl>

Arguments

Arnošt Komárek <a href="/link/arnost.komarek%40mff.cuni.cz?package=mixAK&version=5.4" data-mini-rdoc="mixAK::arnost.komarek@mff.cuni.cz">arnost.komarek@mff.cuni.cz</a>

Author

Handle prior.eps argument of GLMM_MCMC function — GLMM_MCMCprior.eps

<dl>

 <dt>prior.eps</dt>
<dd>see argument<code>prior.eps</code> of
 <code>GLMM_MCMC</code> function</dd>

 <dt>Rc</dt>
<dd>see output element <code>Rc</code> of <code>GLMM_MCMCdata</code>
 function</dd>

 <dt>isigma</dt>
<dd>see output element <code>isigma</code> of <code>GLMM_MCMCifit</code>
 function. It is used to determine a default value of <code>prior.eps$h</code>.
 Defaults to a vector of ones if missing</dd>

 <dt>is.sigma</dt>
<dd>see output element <code>is.sigma</code> of <code>GLMM_MCMCifit</code>
 function</dd>
 
</dl>

Arnošt Komárek <a href='mailto:arnost.komarek@mff.cuni.cz'>arnost.komarek@mff.cuni.cz</a>

GLMM_MCMCprior.eps: Handle prior.eps argument of GLMM_MCMC function

Description

Usage

Value

Arguments

Author

See Also