Atan regularized for the high dimensional Poisson regression model

Document Type : Research Paper


1 College of Administration and Economic, Wasit University, Iraq

2 College of Languages, University of Baghdad, Iraq


Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with  Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.