| Full text | |
| Author(s): |
Ordonez, Jose A.
;
Prates, Marcos O.
;
Bazan, Jorge L.
;
Lachos, Victor H.
Total Authors: 4
|
| Document type: | Journal article |
| Source: | CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE; v. N/A, p. 20-pg., 2023-03-27. |
| Abstract | |
The 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. (AU) | |
| FAPESP's process: | 21/11720-0 - Supervised learning on computer-aided discrete response data with applications in imbalanced data |
| Grantee: | Jorge Luis Bazan Guzman |
| Support Opportunities: | Regular Research Grants |