A0801
Title: Sparse Poisson regression with a penalized weighted score function
Authors: Fang Xie - University of Macau (China) [presenting]
Lihu Xu - University of Macau (China)
Jinzhu Jia - Peking University (China)
Abstract: A new penalized method is proposed to solve sparse Poisson Regression problems. Being different from l1 penalized log-likelihood estimation, our new method can be viewed as a penalized weighted score function method. We show that under mild conditions, our estimator is l1 consistent and the tuning parameter can be pre-specified, which owns the same good property of the square-root Lasso. The simulations show that our proposed method is much more robust than traditional sparse Poisson models using l1 penalized log-likelihood method.
