演讲者：张新雨副研究员 中国科学院数学与系统科学研究院
时间：2017-06-14 11:05-12:05
地点：慧园3栋415报告厅
报告简介：
Considering model averaging estimation in generalized linear models, we propose a weight choice criterion based on the Kullback-Leibler (KL) loss with a penalty term. This criterion is different from that for continuous observations in principle, but reduces to the Mallows criterion in the situation. We prove that the corresponding model averaging estimator is asymptotically optimal under certain assumptions. Numerical experiments illustrate that the proposed method is promising.
