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Nonparametric Bayesian modelling using skewed Dirichlet processes

Authors
Journal
Journal of Statistical Planning and Inference
0378-3758
Publisher
Elsevier
Publication Date
Volume
139
Issue
3
Identifiers
DOI: 10.1016/j.jspi.2008.07.009
Keywords
  • Bayes Factor
  • Density Estimation
  • Dirichlet Process
  • Linear Regression Model
  • Polya Sequence
  • Skewed Distribution
Disciplines
  • Economics

Abstract

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.

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