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INDEPENDENCE DISTRIBUTION-PRESERVING NONNEGATIVE-DEFINITE COVARIANCE STRUCTURES FOR THE SAMPLE VARIANCE |
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| Authors: | Dean M Young Leah M Lehman Laurie M Meaux |
| Institution: | Dept of Information Systems, Baylor University, PO Box 98005, Waco, TX 76798-8005, USA.;Abbott Laboratories, Abbott Park, IL 60064, USA.;Dept of Mathematical Sciences, University of Arkansas, Fayetteville, AR 72701, USA. |
| Abstract: | This paper explicitly characterizes the general nonnegative-definite covariance structure for a multivariate normal random vector such that the univariate sample variance is distributed exactly as if the sample observations are normal independent and identically distributed (i.i.d.). This work extends the results of Baldessari (1965) and Stadje (1984) who have characterized the general positive-definite covariance matrix such that the univariate sample variance is distributed exactly as if the sample observations are normal i.i.d. |
| Keywords: | Quadratic forms central chi-squared random variables independently and identically distributed (i i d ) observations robust statistics |