A New Approach to Estimate the Critical Constant of Selection Procedures-Reference-Cited by-同舟云学术

A New Approach to Estimate the Critical Constant of Selection Procedures

Published:2010-02-07 Issue: Volume:2010 Page:1-12
ISSN:2090-3359
Container-title:Advances in Decision Sciences
language:en
Short-container-title:Advances in Decision Sciences

Author:

Chen E. Jack¹^ORCID,Li Min²

Affiliation:

1. Business Systems, BASF Corporation, 333 Mount Hope Avenue, Rockaway, NJ 07866-0909, USA

2. College of Business Administration, California State University, Sacramento, 6000 J Street, Sacramento, CA 95819-6088, USA

Abstract

A solution to the ranking and selection problem of determining a subset of size containing at least of the best from normal distributions has been developed. The best distributions are those having, for example, (i) the smallest means, or (ii) the smallest variances. This paper reviews various applicable algorithms and supplies the operating constants needed to apply these solutions. The constants are computed using a histogram approximation algorithm and Monte Carlo integration.

Publisher

Asia University

Subject

Applied Mathematics,Computational Mathematics,Statistics and Probability,General Decision Sciences

Link

http://downloads.hindawi.com/archive/2010/948359.pdf

Reference15 articles.

1. Wiley Series in Probability and Statistics: Applied Probability and Statistics,1995

2. Selecting designs with the smallest variance of normal populations

3. Subset selection procedures

4. Estimating steady-state distributions via simulation-generated histograms

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