Premium
SHOULD WE ESTIMATE THE PROBABILITY OF CORRECT SELECTION?
Author(s) -
BOFINGER EVE
Publication year - 1994
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1994.tb00638.x
Subject(s) - selection (genetic algorithm) , confidence interval , inference , coverage probability , statistics , mathematics , bayesian probability , upper and lower bounds , computer science , artificial intelligence , mathematical analysis
Summary Various authors, given k location parameters, have considered lower confidence bounds on (standardized) dserences between the largest and each of the other k ‐ 1 parameters. They have then used these bounds to put lower confidence bounds on the probability of correct selection (PCS) in the same experiment (as was used for finding the lower bounds on differences). It is pointed out that this is an inappropriate inference procedure. Moreover, if the PCS refers to some later experiment it is shown that if a non‐trivial confidence bound is possible then it is already possible to conclude, with greater confidence, that correct selection has occurred in the first experiment. The short answer to the question in the title is therefore ‘No’, but this should be qualified in the case of a Bayesian analysis.