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Probabilistic Divide-and-Conquer: A New Exact Simulation Method, With Integer Partitions as an Example

Part of: Combinatorics Combinatorial probability

Published online by Cambridge University Press:  22 January 2016

RICHARD ARRATIA  and
STEPHEN DeSALVO
RICHARD ARRATIA
Affiliation:
Department of Mathematics, University of Southern California, Los Angeles, CA 90089, USA (e-mail: [email protected])
STEPHEN DeSALVO
Affiliation:
Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90024, USA (e-mail: [email protected])
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Abstract

We propose a new method, probabilistic divide-and-conquer, for improving the success probability in rejection sampling. For the example of integer partitions, there is an ideal recursive scheme which improves the rejection cost from asymptotically order n3/4 to a constant. We show other examples for which a non-recursive, one-time application of probabilistic divide-and-conquer removes a substantial fraction of the rejection sampling cost.

We also present a variation of probabilistic divide-and-conquer for generating i.i.d. samples that exploits features of the coupon collector's problem, in order to obtain a cost that is sublinear in the number of samples.

MSC classification

Primary: 60C05: Combinatorial probability
Secondary: 05A17: Partitions of integers
Type
Paper
Information
Combinatorics, Probability and Computing , Volume 25 , Issue 3 , May 2016 , pp. 324 - 351
Copyright
Copyright © Cambridge University Press 2016 

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