Biased proportional hazard regression estimator in the existence of collinearity
This paper proposed a new biased proportional hazard regression (PHR) estimator which is the combination of elastic net proportional hazard regression (ENPHR) and principal components proportional hazard regression (PCPHR) estimator. Comparison of proposed estimator with ENPHR, PCPHR, ridge PHR, las...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Elsevier
2023-11-01
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Series: | Heliyon |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023086024 |
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author | Anu Sirohi Basim S.O. Alsaedi Marwan H. Ahelali Mahesh Kumar Jayaswal |
author_facet | Anu Sirohi Basim S.O. Alsaedi Marwan H. Ahelali Mahesh Kumar Jayaswal |
author_sort | Anu Sirohi |
collection | DOAJ |
description | This paper proposed a new biased proportional hazard regression (PHR) estimator which is the combination of elastic net proportional hazard regression (ENPHR) and principal components proportional hazard regression (PCPHR) estimator. Comparison of proposed estimator with ENPHR, PCPHR, ridge PHR, lasso PHR, r−k class PHR and maximum likelihood (ML) estimators is done in terms of scalar mean square error (MSE). Simulation study is conducted to examine the performance of each estimator. Furthermore, the developed estimator is utilized to analyze the infant mortality in Delhi, India. |
first_indexed | 2024-03-09T09:19:42Z |
format | Article |
id | doaj.art-668dd775460548a687e2411930ffed03 |
institution | Directory Open Access Journal |
issn | 2405-8440 |
language | English |
last_indexed | 2024-03-09T09:19:42Z |
publishDate | 2023-11-01 |
publisher | Elsevier |
record_format | Article |
series | Heliyon |
spelling | doaj.art-668dd775460548a687e2411930ffed032023-12-02T07:02:06ZengElsevierHeliyon2405-84402023-11-01911e21394Biased proportional hazard regression estimator in the existence of collinearityAnu Sirohi0Basim S.O. Alsaedi1Marwan H. Ahelali2Mahesh Kumar Jayaswal3Department of Statistics, AIAS, Amity University, Noida, India; Corresponding author.Department of Statistics, University of Tabuk, Tabuk 71491, Saudi ArabiaDepartment of Statistics, University of Tabuk, Tabuk 71491, Saudi ArabiaDepartment of Mathematics and Statistics, Banasthali Vidyapith, Rajasthan, IndiaThis paper proposed a new biased proportional hazard regression (PHR) estimator which is the combination of elastic net proportional hazard regression (ENPHR) and principal components proportional hazard regression (PCPHR) estimator. Comparison of proposed estimator with ENPHR, PCPHR, ridge PHR, lasso PHR, r−k class PHR and maximum likelihood (ML) estimators is done in terms of scalar mean square error (MSE). Simulation study is conducted to examine the performance of each estimator. Furthermore, the developed estimator is utilized to analyze the infant mortality in Delhi, India.http://www.sciencedirect.com/science/article/pii/S2405844023086024CollinearityElastic netInfant mortalityPrincipal component regressionProportional hazard regression model |
spellingShingle | Anu Sirohi Basim S.O. Alsaedi Marwan H. Ahelali Mahesh Kumar Jayaswal Biased proportional hazard regression estimator in the existence of collinearity Heliyon Collinearity Elastic net Infant mortality Principal component regression Proportional hazard regression model |
title | Biased proportional hazard regression estimator in the existence of collinearity |
title_full | Biased proportional hazard regression estimator in the existence of collinearity |
title_fullStr | Biased proportional hazard regression estimator in the existence of collinearity |
title_full_unstemmed | Biased proportional hazard regression estimator in the existence of collinearity |
title_short | Biased proportional hazard regression estimator in the existence of collinearity |
title_sort | biased proportional hazard regression estimator in the existence of collinearity |
topic | Collinearity Elastic net Infant mortality Principal component regression Proportional hazard regression model |
url | http://www.sciencedirect.com/science/article/pii/S2405844023086024 |
work_keys_str_mv | AT anusirohi biasedproportionalhazardregressionestimatorintheexistenceofcollinearity AT basimsoalsaedi biasedproportionalhazardregressionestimatorintheexistenceofcollinearity AT marwanhahelali biasedproportionalhazardregressionestimatorintheexistenceofcollinearity AT maheshkumarjayaswal biasedproportionalhazardregressionestimatorintheexistenceofcollinearity |