Exact calculation of minimum sample size for estimating a Poisson parameter

Abstract

We develop an exact approach for the determination of the minimum sample size for estimating a Poisson parameter such that the pre-specified levels of relative precision and confidence are guaranteed. The exact computation is made possible by reducing infinitely many evaluations of coverage probability to finitely many evaluations. The theory for supporting such a reduction is that the minimum of coverage probability with respect to the parameter in an interval is attained at a discrete set of finitely many elements. Computational mechanisms have been developed to further reduce the computational complexity. An explicit bound for the minimum sample size is established.