Accession Number:

ADA210274

Title:

On Lower Confidence for PCS in Truncated Location Parameter Models

Descriptive Note:

Technical rept.

Corporate Author:

PURDUE UNIV LAFAYETTE IN DEPT OF STATISTICS

Report Date:

1989-06-01

Pagination or Media Count:

24.0

Abstract:

We are concerned with deriving lower confidence bounds for the probability of a correct selection in truncated location-parameter models. Two cases are considered according to whether the scale parameter is known or unknown. For each case, a lower confidence bound for the difference between the best and the second best is obtained. These lower confidence bounds are used to construct lower confidence bounds for the probability of a correct selection. The results are then applied to the problem of selecting the best exponential population having the largest Truncated location-parameter. Useful tables are provided for implementing the proposed methods. Keywords Correct selection Probability of a correct selection Indifference zone Lower confidence bound Best population Truncated-location model, Two-parameter exponential distribution.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE