A Selection Procedure for Selecting Good Exponential Populations

✍ Scribed by Amar Nath Gill; Suresh Kumar Sharma

• Publisher: John Wiley and Sons
• Year: 1993
• Tongue: English
• Weight: 333 KB
• Volume: 35
• Category: Article
• ISSN: 0323-3847
• DOI: 10.1002/bimj.4710350312

✦ Synopsis

Abstract

Consider k independent exponential populations with location parameters μ~1~,…, μ~k~ and a common scale parameter or standard deviation θ. Let μ~(k)~ be the largest of the μ's and define a population to be good if its location parameter exceeds μ~(k)~ –Δ~1~. A selection procedure is proposed to select a subset of the k populations which includes the good populations with probability at least P*, a pre‐assigned value. Simultaneous confidence intervals, that can be derived with the proposed selection procedure, are discussed. Moreover, if populations with locations below μ~(k)~ –δ~2~, (δ~2~ > δ~1~) are “bad”, a selection procedure is proposed and a sample size is determined so that the probability of omitting a “good” population or selecting a “bad” population is at most 1 – P*.