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Cluster Weighted Beta Regression: A Simulation Study

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Statistical Learning of Complex Data (CLADAG 2017)

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Abstract

In several application fields, we have to model a response that takes values in a limited range. When these values may be transformed into rates, proportions, concentrations, that is to continuous values in the unit interval, beta regression may be the appropriate choice. In the presence of unobserved heterogeneity, for example when the population of interest is composed by different subgroups, finite mixture of beta regression models could be useful. When conditions of exogeneity of the covariates set are not met, extended modeling approaches should be proposed. For this purpose, we discuss the class of cluster-weighted beta regression models.

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Author information

Authors and Affiliations

  1. Dipartimento di Scienze Statistiche, Sapienza University of Rome, Rome, Italy

    Marco Alfó & Cecilia Vitiello

  2. UNINT, Rome, Italy

    Luciano Nieddu

Authors
  1. Marco Alfó
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  2. Luciano Nieddu
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  3. Cecilia Vitiello
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Corresponding author

Correspondence to Luciano Nieddu .

Editor information

Editors and Affiliations

  1. Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy

    Francesca Greselin

  2. Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy

    Laura Deldossi

  3. Department of Economic and Social Sciences, Università Cattolica del Sacro Cuore, Piacenza, Italy

    Luca Bagnato

  4. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maurizio Vichi

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Alfó, M., Nieddu, L., Vitiello, C. (2019). Cluster Weighted Beta Regression: A Simulation Study. In: Greselin, F., Deldossi, L., Bagnato, L., Vichi, M. (eds) Statistical Learning of Complex Data. CLADAG 2017. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-030-21140-0_1

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