{"id":465,"date":"2022-04-01T00:43:27","date_gmt":"2022-03-31T15:43:27","guid":{"rendered":"http:\/\/ise-hp.ws.hosei.ac.jp\/wp\/?p=465"},"modified":"2022-10-31T14:17:19","modified_gmt":"2022-10-31T05:17:19","slug":"testing-the-order-of-multivariate-normal-mixture-models","status":"publish","type":"post","link":"https:\/\/ise-hp.ws.hosei.ac.jp\/wp\/topics\/465\/","title":{"rendered":"\u516c\u958b\u30bb\u30df\u30ca\u30fc\u306e\u304a\u77e5\u3089\u305b"},"content":{"rendered":"

Testing the Order of Multivariate Normal Mixture Models<\/h3>
Date<\/td>April\/26\/2022<\/td><\/tr>
Time<\/td>Japan Standard Time (UTC+9h)<\/td><\/tr>
\u00a0<\/td>10:50 ~ 12:20<\/td><\/tr>
Speaker<\/td>Katsumi Shimotsu<\/a>\u00a0The University of Tokyo<\/td><\/tr>
Title<\/td>Testing the Order of Multivariate Normal Mixture Models<\/td><\/tr>
Abstract<\/td>Finite mixtures of multivariate normal distributions have been widely used in empirical applications in diverse fields such as statistical genetics and statistical finance. Testing the number of components in multivariate normal mixture models is a long-standing challenge even in the most important case of testing homogeneity. This paper develops a likelihood-based test of the null hypothesis of M components against the alternative hypothesis of M+1 components for a general M>=1. We derive the asymptotic distribution of the proposed EM test statistic under the null hypothesis and local alternatives and show the validity of parametric bootstrap. The simulations show that the proposed test has good finite sample size and power properties.<\/td><\/tr>
Zoom<\/td>Click here to join the Zoom Meeting<\/a>\u00a0Meeting ID: 857 7302 7215 Passcode: 674245<\/td><\/tr>
Venue<\/td>Room E207, East Bldg.,\u00a0Koganei Campus, Hosei University<\/a><\/td><\/tr>
Chair<\/td>Qingfeng Liu<\/a>\u00a0Hosei University<\/td><\/tr>
Hosts<\/td>TEDS and Hosei University<\/td><\/tr><\/tbody><\/table>

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