Bayesian Analysis on Limiting the Student-$t$ Linear Regression Model
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arXiv
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| Format: | Preprint |
| Published: |
2020
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| _version_ | 1866908573839130624 |
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| author | Hayashi, Yoshiko |
| author_facet | Hayashi, Yoshiko |
| contents | For the outlier problem in linear regression models, the Student-$t$ linear regression model is one of the common methods for robust modeling and is widely adopted in the literature. However, most of them applies it without careful theoretical consideration. This study provides the practically useful and quite simple conditions to ensure that the Student-$t$ linear regression model is robust against an outlier in the $y$-direction using regular variation theory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2008_04522 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | Bayesian Analysis on Limiting the Student-$t$ Linear Regression Model Hayashi, Yoshiko Methodology 62J05 For the outlier problem in linear regression models, the Student-$t$ linear regression model is one of the common methods for robust modeling and is widely adopted in the literature. However, most of them applies it without careful theoretical consideration. This study provides the practically useful and quite simple conditions to ensure that the Student-$t$ linear regression model is robust against an outlier in the $y$-direction using regular variation theory. |
| title | Bayesian Analysis on Limiting the Student-$t$ Linear Regression Model |
| topic | Methodology 62J05 |
| url | https://arxiv.org/abs/2008.04522 |