Accession Number:

ADA000253

Title:

On Some Gamma-Minimax Subset Selection and Multiple Comparison Procedures.

Descriptive Note:

Technical rept.,

Corporate Author:

PURDUE UNIV LAFAYETTE IND DEPT OF STATISTICS

Personal Author(s):

• Gupta,Shanti S.
• Huang,Deng-Yuan

Report Date:

1974-11-01

Pagination or Media Count:

20.0

Abstract:

The use of partial or incomplete prior information in statistical inference has led to the development of the gamma-minimax criterion which allows one to select a decision rule that minimizes the maximum expected risk over gamma. In this paper, the authors are concerned with the problem of selecting a subset containing the best population and containing all superior populations and of multiple comparison procedures which are optimal by using gamma-minimax criterion. Some applications are discussed. Asymptotic optimal nonparametric procedures are also considered. Author

Descriptors:

• *STATISTICAL DECISION THEORY
• BAYES THEOREM
• SELECTION
• SET THEORY
• THEOREMS
• MINIMAX TECHNIQUE

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE