Density Regression Based on Proportional Hazards Family
This paper develops a class of density regression models based on proportional hazards family, namely, Gamma transformation proportional hazard (Gt-PH) model . Exact inference for the regression parameters and hazard ratio is derived. These estimators enjoy some good properties such as unbiased esti...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-06-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/17/6/3679 |
| _version_ | 1817994308269113344 |
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| author | Wei Dang Keming Yu |
| author_facet | Wei Dang Keming Yu |
| author_sort | Wei Dang |
| collection | DOAJ |
| description | This paper develops a class of density regression models based on proportional hazards family, namely, Gamma transformation proportional hazard (Gt-PH) model . Exact inference for the regression parameters and hazard ratio is derived. These estimators enjoy some good properties such as unbiased estimation, which may not be shared by other inference methods such as maximum likelihood estimate (MLE). Generalised confidence interval and hypothesis testing for regression parameters are also provided. The method itself is easy to implement in practice. The regression method is also extended to Lasso-based variable selection. |
| first_indexed | 2024-04-14T01:51:13Z |
| format | Article |
| id | doaj.art-fd89ed58c8b04bb4afa5122d5c4411a6 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-14T01:51:13Z |
| publishDate | 2015-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-fd89ed58c8b04bb4afa5122d5c4411a62022-12-22T02:19:21ZengMDPI AGEntropy1099-43002015-06-011763679369110.3390/e17063679e17063679Density Regression Based on Proportional Hazards FamilyWei Dang0Keming Yu1Business School, Shihezi University, Xinjiang, 831300, ChinaSchool of Management, Hefei University of Technology, Hefei, 230009, ChinaThis paper develops a class of density regression models based on proportional hazards family, namely, Gamma transformation proportional hazard (Gt-PH) model . Exact inference for the regression parameters and hazard ratio is derived. These estimators enjoy some good properties such as unbiased estimation, which may not be shared by other inference methods such as maximum likelihood estimate (MLE). Generalised confidence interval and hypothesis testing for regression parameters are also provided. The method itself is easy to implement in practice. The regression method is also extended to Lasso-based variable selection.http://www.mdpi.com/1099-4300/17/6/3679best linear unbiased estimators (BLUE)density regressionexact inferencegamma random variableproportional hazards distribution familyregression analysis |
| spellingShingle | Wei Dang Keming Yu Density Regression Based on Proportional Hazards Family Entropy best linear unbiased estimators (BLUE) density regression exact inference gamma random variable proportional hazards distribution family regression analysis |
| title | Density Regression Based on Proportional Hazards Family |
| title_full | Density Regression Based on Proportional Hazards Family |
| title_fullStr | Density Regression Based on Proportional Hazards Family |
| title_full_unstemmed | Density Regression Based on Proportional Hazards Family |
| title_short | Density Regression Based on Proportional Hazards Family |
| title_sort | density regression based on proportional hazards family |
| topic | best linear unbiased estimators (BLUE) density regression exact inference gamma random variable proportional hazards distribution family regression analysis |
| url | http://www.mdpi.com/1099-4300/17/6/3679 |
| work_keys_str_mv | AT weidang densityregressionbasedonproportionalhazardsfamily AT kemingyu densityregressionbasedonproportionalhazardsfamily |