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On When to Stop Sampling for the Maximum by C. G. E. Boender; A. H. G. Rinnooy Kan is a Computer Science article available to read on EtoBox.

What is On When to Stop Sampling for the Maximum about?

## Suppose a sequential sample is taken from an unknown discrete probability distribution on an unknown range of integers, in an effort to sample its maximum. A crucial issue is an appropriate stopping rule determining when to terminate the sampling process. We approach this problem from a Bayesian perspective, and derive stopping rules that minimize loss functions which assign a loss to the sample size and to the deviation between the maximum in the sample and the true (unknown) maximum. We will show that our rules offer an extremely simple approximate solution to the well-known problem to terminate the Multistart method for continuous global optimization.

Who reads On When to Stop Sampling for the Maximum?

Author

C. G. E. Boender; A. H. G. Rinnooy Kan

Publisher

Springer US; Springer-Verlag; Kluwer Academic Publishers; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 0925-5001)

Published

1991

Language

EN

Field

Computer Science (Physical Sciences)