dmbc_logLik_rbmds

<code>dmbc_logLik_rbmds()</code> computes the log-likelihood value for a DMBC model.

Functions for fitting a Bayesian model for grouping binary
dissimilarity matrices in homogeneous clusters. Currently, it includes
methods only for binary data (<doi:10.18637/jss.v100.i16>).

Sergio Venturini

dmbc

Model Based Clustering of Binary Dissimilarity Measurements

Raffaella Piccarreta

dmbc_logLik_rbmds function

<dl><dt>D</dt>
<dd>A list whose elements are the dissimilarity matrices corresponding
to the judgments expressed by the S subjects/raters. These matrices
must be defined as a <code>dist</code> object.</dd>
<dt>Z</dt>
<dd>A numeric matrix containing the latent configuration.</dd>
<dt>alpha</dt>
<dd>A numeric vector containing the alpha values.</dd></dl>

Arguments

Sergio Venturini <a href="/link/sergio.venturini%40unicatt.it?package=dmbc&version=1.0.3" data-mini-rdoc="dmbc::sergio.venturini@unicatt.it">sergio.venturini@unicatt.it</a>

Author

Log-likelihood for DMBC models. — dmbc_logLik_rbmds

<dl>

<dt>D</dt>
<dd>A list whose elements are the dissimilarity matrices corresponding
to the judgments expressed by the S subjects/raters. These matrices
must be defined as a <code>dist</code> object.</dd>


<dt>Z</dt>
<dd>A numeric matrix containing the latent configuration.</dd>


<dt>alpha</dt>
<dd>A numeric vector containing the alpha values.</dd>

</dl>

Sergio Venturini <a href='mailto:sergio.venturini@unicatt.it'>sergio.venturini@unicatt.it</a>

dmbc_logLik_rbmds: Log-likelihood for DMBC models.

Description

Usage

Value

Arguments

Author

References

See Also