Operating Characteristics of Subset Selection Rules for Exponential Population Threshold Parameters

This article provides the operating characteristics (OCs) of two subset selection rules for exponential populations having a common known scale parameter and possibly differing threshold parameters. One selection rule is based on the minimum sample values and the other is based on the mean (or sum) of the sample values. The random samples drawn from the populations are of equal size. The goal of the selection rules is to choose a subset of the populations such that the population possessing the largest threshold parameter (the “best” population) is contained in the subset with a probability no less than a user prescribed value P*. A correct selection occurs if the best population is contained in the selected subset. The OCs are the probability of a CS and the expected size of the selected subset. The OCs are calculated and compared for several formulations of the selection rules and for two threshold parameter configurations—slippage, and equi-spaced. The computer R-codes for all calculations are given in the Appendices.

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Journal
Applied Mathematics
Published
2025-01-01
DOI
https://doi.org/10.4236/am.2025.165024
Citations
1
Primary Topic
Bayesian Methods and Mixture Models
Type
article
Field-Weighted Citation Impact
2.48
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article

Operating Characteristics of Subset Selection Rules for Exponential Population Threshold Parameters

Gary C. McDonald, Jezerca Hodaj
1 citations
Applied Mathematics
Bayesian Methods and Mixture Models
2.48
article

Operating Characteristics of Subset Selection Rules for Exponential Population Threshold Parameters

Gary C. McDonald, Jezerca Hodaj
article en
1 citations

Abstract

This article provides the operating characteristics (OCs) of two subset selection rules for exponential populations having a common known scale parameter and possibly differing threshold parameters. One selection rule is based on the minimum sample values and the other is based on the mean (or sum) of the sample values. The random samples drawn from the populations are of equal size. The goal of the selection rules is to choose a subset of the populations such that the population possessing the largest threshold parameter (the “best” population) is contained in the subset with a probability no less than a user prescribed value P*. A correct selection occurs if the best population is contained in the selected subset. The OCs are the probability of a CS and the expected size of the selected subset. The OCs are calculated and compared for several formulations of the selection rules and for two threshold parameter configurations—slippage, and equi-spaced. The computer R-codes for all calculations are given in the Appendices.

Applied MathematicsVol. 16(05)
Oakland University (US)
Openalex Percentile: Top 10%
Bayesian Methods and Mixture Models
2.48
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Operating Characteristics of Subset Selection Rules for Exponential Population Threshold Parameters — Gary C. McDonald, Jezerca Hodaj · Applied Mathematics (2025) | TGRS Research Map | TGRS