A random-size subset approach to the selection problem
A random-size subset approach to the selection problem
The problem considered is to select the best population from among a finite number of populations. A new approach is proposed which is to select a random-size subset of populations that will contain the best population with a preassigned probability. This new approach is intuitively natural and needs no tables. For illustration, it is applied to four specific problems: the normal distribution with the largest mean, the normal distribution with the largest absolute value of mean, the Bernoulli distribution with the largest success probability, and the coin with the largest bias
subset selection, indifference zone, monotone likelihood ratio
153-164
Liu, W.
b64150aa-d935-4209-804d-24c1b97e024a
15 November 1995
Liu, W.
b64150aa-d935-4209-804d-24c1b97e024a
Liu, W.
(1995)
A random-size subset approach to the selection problem.
Journal of Statistical Planning and Inference, 48 (2), .
(doi:10.1016/0378-3758(94)00149-P).
Abstract
The problem considered is to select the best population from among a finite number of populations. A new approach is proposed which is to select a random-size subset of populations that will contain the best population with a preassigned probability. This new approach is intuitively natural and needs no tables. For illustration, it is applied to four specific problems: the normal distribution with the largest mean, the normal distribution with the largest absolute value of mean, the Bernoulli distribution with the largest success probability, and the coin with the largest bias
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Published date: 15 November 1995
Keywords:
subset selection, indifference zone, monotone likelihood ratio
Organisations:
Statistical Sciences Research Institute
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Local EPrints ID: 381059
URI: http://eprints.soton.ac.uk/id/eprint/381059
ISSN: 0378-3758
PURE UUID: 428ff86e-92f3-41b2-b896-d36d0b325d09
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Date deposited: 28 Sep 2015 11:11
Last modified: 15 Mar 2024 02:43
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