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A Restricted Subset Selection Rule for Selecting at Least One of the t Best Normal Populations in Terms of Their Means When Their Common Variance is Known, Case II

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  • Pinyuen Chen
  • Lifang Hsu
  • S. Panchapakesan

Abstract

Consider k( ⩾ 2) normal populations with unknown means μ1, …, μk, and a common known variance σ2. Let μ[1] ⩽ ⋅⋅⋅ ⩽ μ[k] denote the ordered μi.The populations associated with the t(1 ⩽ t ⩽ k − 1) largest means are called the t best populations. Hsu and Panchapakesan (2004) proposed and investigated a procedure RHPfor selecting a non empty subset of the k populations whose size is at most m(1 ⩽ m ⩽ k − t) so that at least one of the t best populations is included in the selected subset with a minimum guaranteed probability P* whenever μ[k − t + 1] − μ[k − t] ⩾ δ*, where P* and δ* are specified in advance of the experiment. This probability requirement is known as the indifference-zone probability requirement. In the present article, we investigate the same procedure RHP for the same goal as before but when k − t

Suggested Citation

  • Pinyuen Chen & Lifang Hsu & S. Panchapakesan, 2014. "A Restricted Subset Selection Rule for Selecting at Least One of the t Best Normal Populations in Terms of Their Means When Their Common Variance is Known, Case II," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(10-12), pages 2250-2259, May.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:10-12:p:2250-2259
    DOI: 10.1080/03610926.2013.827717
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