fastCUB_package

<p>The package implements Louis' identity for CUB models for rating data, to retrieve the observed information matrix 
within the Expectation-Maximization algorithm. On this basis, an acceleration strategy is derived and then a best-subset search through 
the covariate space for feeling and uncertainty is implemented.</p>

package

For ordinal rating data, consider the accelerated Expectation-Maximization 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 for CUB regression models is then implemented on such basis. The methods here implemented are illustrated and discussed in the preprint available from Researchgate by Simone R. (2020) <https://tinyurl.com/vvk563e>.

Rosaria Simone

FastCUB

Package:	fastCUB
Type:	Package
Version:	0.0.2
Date:	2019-03-05

fastCUB_package: fastCUB package

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