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A Bayesian semiparametric model for non negative semicontinuous data

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  • Emanuela Dreassi
  • Emilia Rocco

Abstract

When the target variable exhibits a semicontinuous behavior (a point mass in a single value and a continuous distribution elsewhere), parametric “two-part models” have been extensively used and investigated. The applications have mainly been related to non negative variables with a point mass in zero (zero-inflated data). In this article, a semiparametric Bayesian two-part model for dealing with such variables is proposed. The model allows a semiparametric expression for the two parts of the model by using Dirichlet processes. A motivating example, based on grape wine production in Tuscany (an Italian region), is used to show the capabilities of the model. Finally, two simulation experiments evaluate the model. Results show a satisfactory performance of the suggested approach for modeling and predicting semicontinuous data when parametric assumptions are not reasonable.

Suggested Citation

  • Emanuela Dreassi & Emilia Rocco, 2017. "A Bayesian semiparametric model for non negative semicontinuous data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(10), pages 5133-5146, May.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:10:p:5133-5146
    DOI: 10.1080/03610926.2015.1096389
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