Confidence Intervals for Signal to Noise Ratio of a Poisson Distribution

Abstract

The Poisson distribution is one of the most useful probability distributions to fit rare event data. Confidence interval for the SNR is an important issue among the researchers in image processing. This study considers several confidence intervals for the SNR of a Poisson distribution. Different confidence intervals available in literature are reviewed and compared based on the coverage probability and average width of the intervals. Since a theoretical comparison is not possible, a simulation study has been conducted to compare the performance of the interval estimators. Based on the simulation study we observed that most of our proposed interval estimators are performing well in the sense of attaining nominal size and they have been recommended for the researchers. Most of the proposed intervals except methods Wald, Waldz and bootstrap are performing well in the sense of attaining nominal size. The exact method performed the best followed by VSS, Wald B and Bayes in the sense of attaining nominal size and shorter width when the SNR is large.