Statistical Multiple-Decision Procedures for Some Multivariate Selection Problems

Abstract

The following statistical multiple-decision problems are considered for a multivariate normal distribution with unknown (or partially known) covariance matrix, using the indifference-zone and subset approaches: (a) Selecting the variate with the largest population mean; (b) selecting the variate with the smallest population variance; (c) selecting the subclass of variates with the smallest population generalized variance; (d) selecting the population with the smallest vector coefficient of alienation between two subclasses of variates; (e) selecting the best subclass of predictors for a specified subclass of variates. Small-sample theory is employed in (a) and (b), while large-sample theory is used in (b), (c), (d) and (e). (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1973
Accession Number
AD0766469

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  • Ricardo M. Frischtak

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  • Cornell University

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  • C4I

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  • Coefficients
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  • Mathematics

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