Back to Search
Start Over
Bayesian modeling of location, scale, and shape parameters in skew‐normal regression models.
- Source :
-
Statistical Analysis & Data Mining . Feb2022, Vol. 15 Issue 1, p98-111. 14p. - Publication Year :
- 2022
-
Abstract
- In this paper, we propose Bayesian skew‐normal regression models where the location, scale and shape parameters follow (linear or nonlinear) regression structures, and the variable of interest follows the Azzalini skew‐normal distribution. A Bayesian method is developed to fit the proposed models, using working variables to build the kernel transition functions. To illustrate the performance of the proposed Bayesian method and application of the model to analyze statistical data, we present results of simulated studies and of the application to studies of forced displacement in Colombia. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19321864
- Volume :
- 15
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Statistical Analysis & Data Mining
- Publication Type :
- Academic Journal
- Accession number :
- 154579535
- Full Text :
- https://doi.org/10.1002/sam.11548