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A Bayesian semi-parametric approach to the ordinal calibration problem

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  • María Paz Casanova
  • Yasna Orellana

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.

Suggested Citation

  • María Paz Casanova & Yasna Orellana, 2016. "A Bayesian semi-parametric approach to the ordinal calibration problem," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(22), pages 6596-6610, November.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:22:p:6596-6610
    DOI: 10.1080/03610926.2014.963617
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