統計学輪講のスケジュールに戻る．日時 2003年 2月10日(火) 15時〜16時40分
場所 経済学部新棟３階第３教室
講演者 Prof. M.S. Srivastava (University of Toronto)
演題 Multivariate Theory For Analyzing High-Dimensional Data
概要
In this talk I give multivariate theory for analyzing high-dimensional
data. Such data arise, for example, in DNA microarrays where there are
observations on thousands of genes but only on few subjects/patients.
Theory and methods for reducing the dimension and drawing inference from
them will be presented. The inference problems include one-sample,
two-sample, and MANOVA tests. A sample measure of distance between two
populations is defined. This sample squared distance is used in classifying
an individual with p-vector observation into one of several multivariate
populations by minimum distance rule.
統計学輪講のスケジュールに戻る．
Tokyo University