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

Pinyuen Chen, Lifang Hsu and S. Panchapakesan

Communications in Statistics - Theory and Methods, 2014, vol. 43, issue 10-12, 2250-2259

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

Date: 2014
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DOI: 10.1080/03610926.2013.827717

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