Penalized complexity priors for the skewness parameter of power links

Author:

Ordoñez José A.1,Prates Marcos O.2,Bazán Jorge L.3,Lachos Victor H.4ORCID

Affiliation:

1. Departamento de Estatística Universidade Estadual de Campinas Campinas São Paulo Brazil

2. Departamento de Estatística Universidade Federal de Minas Gerais Belo Horizonte Minas Gerais Brazil

3. Departamento de Matemática Aplicada e Estatística Universidade de São Paulo São Carlos São Paulo Brazil

4. Department of Statistics University of Connecticut Storrs CT‐06269 Connecticut U.S.A.

Abstract

AbstractThe choice of a prior distribution is a key aspect of the Bayesian method. However, in many cases, such as the family of power links, this is not trivial. In this article, we introduce a penalized complexity prior (PC prior) of the skewness parameter for this family, which is useful for dealing with imbalanced data. We derive a general expression for this density and show its usefulness for some particular cases such as the power logit and the power probit links. A simulation study and a real data application are used to assess the efficiency of the introduced densities in comparison with the Gaussian and uniform priors. Results show improvement in point and credible interval estimation for the considered models when using the PC prior in comparison to other well‐known standard priors.

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance of evaluation metrics for classification in imbalanced data;Computational Statistics;2024-08-24

2. Asymmetric Binary Regression Models for Imbalanced Datasets: An Application to Students’ Churn;Studies in Classification, Data Analysis, and Knowledge Organization;2024

3. Longitudinal binary response models using alternative links for medical data;Brazilian Journal of Probability and Statistics;2023-06-01

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