One major obstacle in applications of Stein’s method for compound Poisson approximation is the availability of so-called magic factors (bounds on the solution of the Stein equation) with favourable dependence on the parameters of the approximating compound Poisson random variable. In general, the best such bounds have an exponential dependence on these parameters, though in certain situations better bounds are available. In this paper, we extend the region for which well-behaved magic factors are available for compound Poisson approximation in the Kolmogorov metric, allowing useful compound Poisson approximation theorems to be established in some regimes where they were previously unavailable. To illustrate the advantages offered by these new bounds, we consider applications to runs, reliability systems, Poisson mixtures and sums of independent random variables.
|Number of pages||10|
|Journal||Electronic Communications in Probability|
|Early online date||23 Nov 2017|
|Publication status||Published - 2017|
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Fraser A. Daly
- School of Mathematical & Computer Sciences - Associate Professor
- School of Mathematical & Computer Sciences, Actuarial Mathematics & Statistics - Associate Professor
Person: Academic (Research & Teaching)