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- W21872344 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. Our goal is to select 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 populations associated with the t (1 ≤ t ≤ k − 1) largest means 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. Santner (1976) proposed and investigated a procedure (R s) based on samples of size n from each of the populations. We propose and investigate an alternative procedure R hp with the same sampling scheme. We compare our rule with that of a procedure that selects a subset of fixed size m. The special case of t = 1 was earlier studied by Gupta and Santner (1973) and Hsu and Panchapakesan (2003)." @default.
- W21872344 created "2016-06-24" @default.
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- W21872344 date "2007-12-27" @default.
- W21872344 modified "2023-09-23" @default.
- W21872344 title "A Restricted Subset Selection Rule for Selecting At Least One of the t Best Normal Populations in Terms of Their Means: Common Known Variance Case" @default.
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- W21872344 doi "https://doi.org/10.1007/0-8176-4422-9_7" @default.
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