Accession Number:

AD0780892

Title:

A Generalized Goal in Restricted Subset Selection Theory

Descriptive Note:

Technical rept.

Corporate Author:

CORNELL UNIV ITHACA NY DEPT OF OPERATIONS RESEARCH

Personal Author(s):

• Santner, Thomas J.

Report Date:

1974-05-01

Pagination or Media Count:

26.0

Abstract:

A class of multiple decision procedures which selects a random size subset of populations not exceeding m determined a priori in size has previously been considered for the problem of selecting the best population among k candidates. The present paper generalizes the earlier results to the goal of selecting at least one of the t best populations. Applications of the basic theory can be made to many specific problems considered in the literature. In the regular case these include selection from univariate normal populations for means and variances, from gamma populations for scale factors and from noncentral chi square or noncentral F populations for noncentrality parameters and in the nonregular case selection from uniform populations with different supports.

Descriptors:

• *SAMPLING
• *STATISTICAL DECISION THEORY
• ANALYSIS OF VARIANCE
• PROBABILITY
• SELECTION
• SET THEORY

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE