JSM 2005 - Toronto

Abstract #303453

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 135
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #303453
Title: A Characterization of Multivariate Normal Distribution with Special Covariance Structure
Author(s): Dhanuja Kasturiranta*+ and Truc T. Nguyen and Arjun K. Gupta
Companies: Bowling Green State University and Bowling Green State University and Bowling Green State University
Address: DEPARTMENT OF MATH AND STAT, BOWLING GREEN, OH, 43403,
Keywords: characterization ; EDF goodness-of-fit tests
Abstract:

In the multivariate linear regression, we assume the error random vectors are independently and identically distributed as normal with mean zero and constant variance. In the case of variance-covariance structure, the error vectors are known up to a scalar multiple. To test whether a set of observed data is from the multivariate regression model, we need to construct a test for testing the hypothesis that the observations are normally distributed with unknown mean and partially known covariance structure. A characterization of this model is given and application of this result in constructing EDF goodness-of-fit tests is discussed.

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