Year: 2014
Type: preprint
Abstract: When the target variable exhibits a semicontinuous behaviour (i.e. a point mass in a single value and a continuous distribution elsewhere) parametric `two-part regression models' have been extensively used and investigated. In this paper, a semiparametric Bayesian two-part regression model for dealing with such variables is proposed. The model allows a semiparametric expression for the two part of the model by using Dirichlet processes. A motivating example (in the `small area estimation' framework) based on pseudo-real data on grapewine production in Tuscany, is used to evaluate the capabilities of the model. Results show a satisfactory performance of the suggested approach to model and predict semicontinuous data when parametric assumptions (distributional and/or relationship) are not reasonable.
Source: arXiv (Cornell University)
Authors: Dreassi, Emanuela, Rocco, Emilia
Institution: University of Florence
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2264287806