Journal article

On negative binomial approximation to k-runs

Xiaoxin Wang, Aihua Xia

JOURNAL OF APPLIED PROBABILITY | CAMBRIDGE UNIV PRESS | Published : 2008

Abstract

The distributions of the run occurrences for a sequence of independent and identically distributed (i.i.d.) experiments are usually obtained by combinatorial methods (see Balakrishnan and Koutras (2002, Chapter 5)) and the resulting formulae are often very tedious, while the distributions for non i.i.d. experiments are generally intractable. It is therefore of practical interest to find a suitable approximate model with reasonable approximation accuracy. In this paper we demonstrate that the negative binomial distribution is the most suitable approximate model for the number of k-runs: it outperforms the Poisson approximation, the general compound Poisson approximation as observed in Eichels..

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University of Melbourne Researchers