fastcub00

Function to estimate and validate a CUB model without covariates for given ordinal responses.

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

fastcub00 function

<dl><dt>m</dt>
<dd>Number of ordinal categories</dd>
<dt>ordinal</dt>
<dd>Vector of ordinal responses</dd>
<dt>starting</dt>
<dd>Starting values for the algorithm</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>
<dt>iterc</dt>
<dd>Iteration from which the acceleration strategy starts</dd>
<dt>invgen</dt>
<dd>Logical: should the recursive formula for the inverse of the information matrix be considered? (Default is TRUE)</dd></dl>

Arguments

Main function for CUB models without covariates — fastcub00

<dl>

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


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


<dt>starting</dt>
<dd>Starting values for the algorithm</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>


<dt>iterc</dt>
<dd>Iteration from which the acceleration strategy starts</dd>


<dt>invgen</dt>
<dd>Logical: should the recursive formula for the inverse of the information matrix be considered? (Default is TRUE)</dd>

</dl>

fastcub00: Main function for CUB models without covariates

Description

Usage

Value

Arguments

See Also