Sequential Estimation of the Largest Normal Mean When the Variance is Known

Abstract

Given n observations from each of k normal populations with common known variance (sigma squared), the value of the largest of the k means (whose values are not known) is to be estimated using the largest value of the k sample means. It is desired to design a sampling rule which guarantees that the Mean Squared Error (M.S.E.) of the estimate does not exceed a given bound regardless of the configuration of values of the k means.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1973
Accession Number
AD0757094

Entities

People

  • Saul Blumenthal

Organizations

  • Cornell University

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  • Data Science
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  • Probability
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Fields of Study

  • Mathematics

Readers

  • Regression Analysis.