Statistics Seminar: STA 290
Thursday, May 17th, 2012 at 4:10pm, MSB 1147 (Colloquium Room)
Refreshments at 3:30pm prior to seminar in MSB 4110 (Statistics Lounge)
Speaker: Debashis Paul (Statistics, UC Davis)
Title: A regularization of Hotelling's $T^2$ for high-dimensional data
Abstract: We consider the classical problem of testing for the mean vector of a multivariate normal distribution when the covariance matrix is unknown. A well-known test procedure is the Hotelling's $T^2$ test. But it is not well-defined when the dimension is larger than the sample size. We consider a regularized version of the Hotelling's $T^2$ statistic through a modification of the sample covariance matrix similar to what is done in ridge regression.We study the properties of the proposed test procedures under the scenario when the dimension and sample sizes are comparable and compare them with various other tests proposed in the literature.