Mixture models for rating data: the method of moments via Groebner bases

  • Maria Iannario Università degli Studi di Napoli Federico II
  • Rosaria Simone Università degli Studi di Napoli Federico II
Keywords: Ordinal data, Groebner bases, Method of moments, Uncertainty, Overdispersion.

Abstract

 

A recent thread of research in ordinal data analysis involves a class of mixture models that designs the responses as the combination of the two main aspects driving the decision pro- cess: a feeling and an uncertainty components. This novel paradigm has been proven flexible to account also for overdispersion. In this context, Groebner bases are exploited to estimate model parameters by implementing the method of moments. In order to strengthen the validity of the moment procedure so derived, alternatives parameter estimates are tested by means of a simulation experiment. Results show that the moment estimators are satisfactory per se, and that they significantly reduce the bias and perform more efficiently than others when they are set as starting values for the Expectation-Maximization algorithm. 

Author Biographies

Maria Iannario, Università degli Studi di Napoli Federico II

Dipartimento di Scienze Politiche

Rosaria Simone, Università degli Studi di Napoli Federico II

Dipartimento di Scienze Politiche

Researcher in Statistics

Published
2017-12-26
Section
Articles