
The accuracy of compound Poisson approximation can be estimated using Stein's method in terms of quantities similar to those which must be calculated for Poisson approximation. However, the solutions of the relevant Stein equation may, in general, grow exponentially fast with the mean number of ‘clumps’, leading to many applications in which the bounds are of little use. In this paper, we introduce a method for circumventing this difficulty. We establish good bounds for those solutions of the Stein equation which are needed to measure the accuracy of approximation with respect to Kolmogorov distance, but only in a restricted range of the argument. The restriction on the range is then compensated by a truncation argument. Examples are given to show that the method clearly outperforms its competitors, as soon as the mean number of clumps is even moderately large.
10123 Institute of Mathematics, 510 Mathematics, 2604 Applied Mathematics, truncation argument, compound Poisson, Central limit and other weak theorems, Stein's method, distributional approximation, 2613 Statistics and Probability, Approximations to statistical distributions (nonasymptotic)
10123 Institute of Mathematics, 510 Mathematics, 2604 Applied Mathematics, truncation argument, compound Poisson, Central limit and other weak theorems, Stein's method, distributional approximation, 2613 Statistics and Probability, Approximations to statistical distributions (nonasymptotic)
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