Abstract
In the past few years, mathematicians have developed a powerful technique known as the Chen-Stein method [2, 4] for approximating the distribution of a sum of weakly dependent Bernoulli random variables. In contrast to many asymptotic methods, this approximation carries with it explicit error bounds. Let X α be a Bernoulli random variable with success probability p α where a ranges over some finite index set I. It is natural to speculate that the sum S = Σα∈1 X α is approximately Poisson with mean λ = Σα∈I p α. The Chen-Stein method estimates the error in this approximation using the total variation distance between two integer-valued random variables Y and Z.
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Lange, K. (1997). Poisson Approximation. In: Mathematical and Statistical Methods for Genetic Analysis. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2739-5_13
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DOI: https://doi.org/10.1007/978-1-4757-2739-5_13
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