Nonparametric Bayesian modelling using skewed Dirichlet processes

Iglesias, PL; Orellana, Y; Quintana, FA

Abstract

We introduce a new class of discrete random probability measures that extend the definition of Dirichlet process (DP) by explicitly incorporating skewness. The asymmetry is controlled by a single parameter in such a way that symmetric DPs are obtained as a special case of the general construction. We review the main properties of skewed DPs and develop appropriate Polya urn schemes. We illustrate the modelling in the context of linear regression models of the capital asset pricing model (CAPM) type, where assessing symmetry for the error distribution is important to check validity of the model. © 2008 Elsevier B.V. All rights reserved.

Más información

Título según WOS: Nonparametric Bayesian modelling using skewed Dirichlet processes
Título según SCOPUS: Nonparametric Bayesian modelling using skewed Dirichlet processes
Título de la Revista: JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volumen: 139
Número: 3
Editorial: Elservier
Fecha de publicación: 2009
Página de inicio: 1203
Página final: 1214
Idioma: English
URL: http://linkinghub.elsevier.com/retrieve/pii/S0378375808003029
DOI:

10.1016/j.jspi.2008.07.009

Notas: ISI, SCOPUS