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Penalized Poisson Regression Model using adaptive modified Elastic Net Penalty

Algamal, Zakariya Yahya and Lee, Muhammad Hisyam (2015) Penalized Poisson Regression Model using adaptive modified Elastic Net Penalty. Electronic Jourl Of Applied Statistical Alysis, 8 (2). pp. 236-245. ISSN 2052-336X

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Official URL: http://dx.doi.org/10.1285/i20705948v8n2p236

Abstract

Variable selection in count data using penalized Poisson regression is one of the challenges in applying Poisson regression model when the explanatory variables are correlated. To tackle both estimate the coefficients and perform variable selection simultaneously, elastic net penalty was successfully applied in Poisson regression. However, elastic net has two major limitations. First it does not encouraging grouping effects when there is no large correlation. Second, it is not consistent in variable selection. To address these issues, a modification of the elastic net (AEN) and its adaptive modified elastic net (AAEM), are proposed to take into account the weak and mild correlation between explanatory variables and to provide the consistency of the variable selection simultaneously. Our simulation and real data results show that AEN and AAEN have advantage with weak, mild, and extremely correlated variables in terms of both prediction and variable selection consistency comparing with other existing penalized methods.

Item Type:Article
Uncontrolled Keywords:elastic net, high dimensional, LASSO, penalization, poisson regression
Subjects:A General Works
ID Code:58771
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:21 Feb 2017 16:20

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