An adaptive approach is considered as an alternative to the classical indifference-zone formulation of the problems of ranking and selection. With a fixed $\gamma^\ast$, the proposed procedure calls for the termination of sampling when the estimated probability of correct selection exceeds $\gamma^\ast$ for the first time. Asymptotic properties of this procedure are proved as $\gamma^\ast \rightarrow 1$, and Monte Carlo results show that the procedure is well behaved even for moderate $\gamma^\ast$. Since the stopping variables depend on the estimators of the ordered parameters, distributions of the estimators as functions of the parameters are carefully studied via majorization.
Publié le : 1978-05-14
Classification:
Sequential multiple decision rules,
ranking and selection,
adaptive methods,
sequential estimation,
majorization and spacings,
62F07,
62L12
@article{1176344210,
author = {Tong, Y. L.},
title = {An Adaptive Solution to Ranking and Selection Problems},
journal = {Ann. Statist.},
volume = {6},
number = {1},
year = {1978},
pages = { 658-672},
language = {en},
url = {http://dml.mathdoc.fr/item/1176344210}
}
Tong, Y. L. An Adaptive Solution to Ranking and Selection Problems. Ann. Statist., Tome 6 (1978) no. 1, pp. 658-672. http://gdmltest.u-ga.fr/item/1176344210/