Sparse Poisson regression with penalized weighted score function

Abstract

By introducing a weighted score function, we propose a new penalized method, similar to square root lasso, to study sparse Poisson regression problems. The corresponding new estimator not only has $\ell _{1}$ consistency but also enjoys the tuning free property. We further verify our theoretical results by numerical simulations and apply them to an image reconstruction problem.