loglikcubp0

Compute the log-likelihood function of a CUB model fitting ordinal responses with covariates
for explaining the uncertainty component.

internal

For ordinal rating data, consider the accelerated EM algorithm to estimate and test models within the family of
CUB models (where CUB stands for Combination of a
discrete Uniform and a shifted Binomial distributions). The procedure is built upon Louis' identity for the observed information matrix. Best-subset variable selection is then implemented since it becomes more feasible from the computational point of view.

Rosaria Simone

FastCUB

Fast Estimation of CUB Models via Louis' Identity

loglikcubp0 function

<dl><dt>m</dt>
<dd>Number of ordinal categories</dd>
<dt>ordinal</dt>
<dd>Vector of ordinal responses</dd>
<dt>Y</dt>
<dd>Matrix of selected covariates for explaining the uncertainty component</dd>
<dt>bbet</dt>
<dd>Vector of parameters for the uncertainty component, with length equal to
NCOL(Y)+1 to account for an intercept term (first entry of bbet)</dd>
<dt>ccsi</dt>
<dd>Feeling parameter</dd></dl>

Arguments

Log-likelihood function of a CUB model with covariates for the uncertainty component — loglikcubp0

<dl>

<dt>m</dt>
<dd>Number of ordinal categories</dd>


<dt>ordinal</dt>
<dd>Vector of ordinal responses</dd>


<dt>Y</dt>
<dd>Matrix of selected covariates for explaining the uncertainty component</dd>


<dt>bbet</dt>
<dd>Vector of parameters for the uncertainty component, with length equal to
NCOL(Y)+1 to account for an intercept term (first entry of bbet)</dd>


<dt>ccsi</dt>
<dd>Feeling parameter</dd>

</dl>

loglikcubp0: Log-likelihood function of a CUB model with covariates for the uncertainty component

Description

Usage

Arguments