A Bayesian semi-parametric approach to the ordinal calibration problem. Issue 22 (16th November 2016)

• Record Type: Journal Article
• Authors: Casanova, María Paz; Orellana, Yasna
• Is Part Of: Communications in statistics. Volume 45:Issue 22(2016)
• Page Start: 6596
• Page End: 6610
• Publication Date: 2016-11-16
• Subjects: Calibration problem -- MCMC -- Ordinal regression -- Skewed Dirichlet processes; 62G86; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2014.963617
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: We introduce a semi-parametric Bayesian approach based on skewed Dirichlet processes priors for location parameters in the ordinal calibration problem. This approach allows the modeling of asymmetrical error distributions. Conditional posterior distributions are implemented, thus allowing the use of Markov chains Monte Carlo to generate the posterior distributions. The methodology is applied to both simulated and real data.