cubecsi

Estimate and validate a CUBE model for ordinal data, with covariates only for explaining the
feeling component.

internal

#models

For ordinal rating data, estimate and test models within the family of CUB models and their extensions (where CUB stands for Combination of a discrete Uniform and a shifted Binomial distributions); Simulation routines, plotting facilities and fitting measures are also provided.

Rosaria Simone

A Class of Mixture Models for Ordinal Data

Maria Iannario

Domenico Piccolo

cubecsi function

<dl><dt>m</dt>
<dd>Number of ordinal categories</dd>
<dt>ordinal</dt>
<dd>Vector of ordinal responses</dd>
<dt>W</dt>
<dd>Matrix of selected covariates for explaining the feeling component</dd>
<dt>starting</dt>
<dd>Vector of initial parameters estimates to start the optimization algorithm, with length equal to
NCOL(W) + 3 to account for an intercept term for the feeling component (first entry)</dd>
<dt>maxiter</dt>
<dd>Maximum number of iterations allowed for running the optimization algorithm</dd>
<dt>toler</dt>
<dd>Fixed error tolerance for final estimates</dd></dl>

Arguments

Main function for CUBE models with covariates only for feeling — cubecsi

<dl>

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


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


<dt>W</dt>
<dd>Matrix of selected covariates for explaining the feeling component</dd>


<dt>starting</dt>
<dd>Vector of initial parameters estimates to start the optimization algorithm, with length equal to
NCOL(W) + 3 to account for an intercept term for the feeling component (first entry)</dd>


<dt>maxiter</dt>
<dd>Maximum number of iterations allowed for running the optimization algorithm</dd>


<dt>toler</dt>
<dd>Fixed error tolerance for final estimates</dd>

</dl>

cubecsi: Main function for CUBE models with covariates only for feeling

Description

Usage

Value

Arguments

See Also