Flexible Robust Mixture Regression Modeling
This paper provides a flexible methodology for the class of finite mixture of regressions with scale mixture of skew-normal errors (SMSN-FMRM) introduced by [42], relaxing the constraints imposed by the authors during the estimation process. Based on the data augmentation principle and Markov chain...
| Published in: | Revstat Statistical Journal |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Instituto Nacional de Estatística | Statistics Portugal
2022-02-01
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| Subjects: | |
| Online Access: | https://revstat.ine.pt/index.php/REVSTAT/article/view/365 |
| Summary: | This paper provides a flexible methodology for the class of finite mixture of regressions with scale mixture of skew-normal errors (SMSN-FMRM) introduced by [42], relaxing the constraints imposed by the authors during the estimation process. Based on the data augmentation principle and Markov chain Monte Carlo (MCMC) algorithms, a Bayesian inference procedure is developed. A simulation study is implemented in order to understand the possible effects caused by the restrictions and an example with a well known dataset illustrates the performance of the proposed methods.
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| ISSN: | 1645-6726 2183-0371 |