Minimum Variance Unbiased Estimators for Poisson Probabilities

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Abstract
This paper considers the problem of estimating Poisson probabilities or relative frequencies and some extensions of that problem. It is shown how minimum variance unbiased estimators based on a simple random sample of 72 observations on a Poisson process may be easily developed. Variances of the estimators and estimators for their variances are derived. Comparisons with maximum likelihood estimators and with distribution-free relative frequency estimators are made and illustrated with two examples.

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