A moment-based criterion for determining the number of components in a normal mixture model

作     者：Yimin Zhou Liyan Han Dan Wang Libo Yin 

作者机构：School of Economics and Management Beihang University Beijing 100191 China School of Instrumentation Science and Opto-electronics Engineering Beihang University Beijing 100191 China School of Finance Central University of Finance and Economics Beijing 100081 China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2017年第28卷第4期

页      面：801-809页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by the National Natural Sciences Foundation of China(71371022 71401193 71671193) the Program for Innovation Research in Central University of Finance and Economics the Innovation Foundation of BUAA for Ph.D.Graduates 

主　　题：information criteria Gaussian mixture moment based number of components 

摘      要：Determining the number of components is a crucial issue in a mixture model. A moment-based criterion is considered to estimate the number of components arising from a normal mixture model. This criterion is derived from an omnibus statistic involving the skewness and kurtosis of each component. The proposed criterion additionally provides a measurement for the model fit in an absolute sense. The performances of our criterion are satisfactory compared with other classical criteria through Monte-Carlo experiments.