On the Independence Jeffreys prior for skew--symmetric models with applications

2013/07/24 by Francisco J. Rubio, Rubio, F. J., Brunero Liseo +1 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.1307.6442

openalex publication_date 2013/07/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We study the Jeffreys prior of the skewness parameter of a general class of scalar skew--symmetric models. It is shown that this prior is symmetric about 0, proper, and with tails O(λ^-3/2) under mild regularity conditions. We also calculate the independence Jeffreys prior for the case with unknown location and scale parameters. Sufficient conditions for the existence of the corresponding posterior distribution are investigated for the case when the sampling model belongs to the family of skew--symmetric scale mixtures of normal distributions. The usefulness of these results is illustrated using the skew--logistic model and two applications with real data.

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