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A composite stopping rule for multinomial subset selection
Author(s) -
Chen Pinyuen,
Hsu Lifang
Publication year - 1991
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1991.tb00971.x
Subject(s) - multinomial distribution , stopping rule , truncation (statistics) , mathematics , sample size determination , sampling (signal processing) , selection (genetic algorithm) , statistics , inverse , sample (material) , sampling design , algorithm , computer science , mathematical optimization , artificial intelligence , population , chemistry , geometry , demography , filter (signal processing) , chromatography , sociology , computer vision
The paper studies a sequential procedure R for selecting a random size subset that contains the multinomial cell which has the largest cell probability. The stopping rule of the proposed procedure R is the composite of the stopping rules of curtailed sampling, inverse sampling, Ramsey–Alam sampling, and the truncation of fixed‐sample‐size procedure. A property on the worst configuration is shown, and it is employed in computing the procedure parameters that guarantee certain probability requirements. Tables of these procedure parameters, the corresponding probability of correct selection, the expected sample size, and the expected subset size are given for comparison.
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