Distribution of the C statistic with applications to the sample mean of Poisson data |
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Authors: | Massimiliano Bonamente |
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Institution: | Department of Physics and Astronomy, University of Alabama in Huntsville, Huntsville, AL, USA |
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Abstract: | The statistic, also known as the Cash statistic, is often used in astronomy for the analysis of low-count Poisson data. The main advantage of this statistic, compared to the more commonly used statistic, is its applicability without the need to combine data points. This feature has made the statistic a very useful method to analyze Poisson data that have small (or even null) counts in each resolution element. One of the challenges of the statistic is that its probability distribution, under the null hypothesis that the data follow a parent model, is not known exactly. This paper presents an effort towards improving our understanding of the statistic by studying (a) the distribution of statistic for a fully specified model, (b) the distribution of Cmin resulting from a maximum-likelihood fit to a simple one-parameter constant model, i.e. a model that represents the sample mean of N Poisson measurements, and (c) the distribution of the associated statistic that is used for parameter estimation. The results confirm the expectation that, in the high-count limit, both statistic and Cmin have the same mean and variance as a statistic with same number of degrees of freedom. It is also found that, in the low-count regime, the expectation of the statistic and Cmin can be substantially lower than for a distribution. The paper makes use of recent X-ray observations of the astronomical source PG 1116+215 to illustrate the application of the statistic to Poisson data. |
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Keywords: | Random effects probability statistics |
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