主 题：Model Selection for Gaussian Mixture Models
主讲人： Associate Prof. Heng Peng
主持人：林华珍教授
时 间：2015年11月13日上午10：30-11：30
地 点：西南财经大学柳林校区 颐德楼多媒体教室H414
主办单位：统计研究中心 统计学院 科研处
主讲人简介：
Heng Peng The Hong Kong Baptist University 副教授，目前是Member of Institute of Mathematical Statistics. Associate Editor of Statistica Sinica，发表文章36篇，其中在JASA 、JRSS(B) 、The Annals of Statistics、Biometrika等国际顶级期刊上发表论文10篇。
内容提要：
This paper is concerned with an important issue in nite mixture modeling, namely the selection of the number of mixing components. A new penalized likelihood method is proposed for nite multivariate Gaussian mixture models, and it is shown to be statistically consistent in determining the number of components. A modied EM algorithm is developed to simultaneously select the number of components and estimate the mixing probabilities and the unknown parameters of Gaussian distributions. Simulations and a real data analysis are presented to illustrate the performance of the proposed method.
