B0567
Title: Testing Poissonity of many populations
Authors: Maria Dolores Jimenez-Gamero - Universidad de Sevilla (Spain) [presenting]
Jacobo de Una-Alvarez - Universidade de Vigo (Spain)
Abstract: Univariate count data appear in many real-life situations, and the Poisson distribution is frequently used to model this kind of data. Testing the goodness-of-fit of given observations with a probabilistic model is a crucial aspect of data analysis. Because of these reasons, a number of authors have proposed tests for the Poisson law. Most papers on this issue deal with testing Poissonity for a single sample, and the properties of the proposed procedures are studied as the sample size increases. We consider the problem of simultaneously testing Poissonity for $k$ samples, where $k$ can increase with the sample sizes. Moreover, $k$ will be allowed to be even larger than the sample sizes. This is important, for instance, in applications with high-dimensional data, such as those arising from DNA sequencing experiments. The cases of independent samples and weakly dependent samples are both of them studied.
