Gamma-Optimal Decision Procedures for Selecting the Best Population in Randomized Complete Block Design.
Abstract
In randomized complete block design, we face the problem of selecting the best population. If some partial information about the unknown parameters is available, then we wish to determine the optimal decision rule to select the best population. In this paper, in the class of natural selection rules, we employ the gamma-optimal criterion to determine optimal decision rules that will minimize the maximum expected risk over the class of some partial information. Furthermore, the traditional hypothesis testing is briefly discussed from the view point of ranking and selection.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1982
- Accession Number
- ADA120946
Entities
People
- Deng Yuang Huang
- Sheng-tsaing Tseng
Organizations
- Purdue University