重庆大学数学与统计学院：型号和特性选择在半参数模型的A级

　　重庆大学数学与统计学院开设了一场题为“Model and Feature Selection in A Class of Semiparametric Models(型号和特性选择在半参数模型的A级)”的讲座，重庆大学数学与统计学院目前设有数学系、信息与计算科学系、统计与精算系，分别负责三个本科专业——数学与应用数学、信息与计算科学、统计学的建设与人才培养。讲座的主要内容是：

　　选型是一首老歌统计。随着高维近年来激增，人们开始用新的调----的惩罚似然法进行播放。在这次演讲中，Wenyang Zhang教授要研究一类半参数模型的，潜在的解释变量数量的增长比样品尺寸要快。Wenyang Zhang要礼物选择的重要特征，同时确定了正确的模型的新惩罚的可能性程序。我将探讨建议的程序处罚部分的有效性，并提出把罚款的新途径。渐近性质将提交证明拟议的方法。我也表明了该程序的性能时，样本规模是模拟研究有限。最后，Wenyang Zhang将用真实数据的例子说明了该方法的应用。

　　原文：Model selection is an old song in statistics. With the surge of high dimensionality in recent years, people start to play it with a new tune ----the penalised likelihood method. In this talk, I am going to investigate a class of semiparametric models where the number of potential explanatory variables grows much fast than the sample size. I am going present a new penalised likelihood procedure which selects the important features and identifies the correct model simultaneously. I will explore the effectiveness of the penalty part in the proposed procedure, and present a new way to put penalty. Asymptotic properties will be presented to justify the proposed methodology. I will also show the performance of the proposed procedure when sample size is finite by simulation studies. Finally, I will illustrate the application of the proposed method by a real data example.