Volume 18, 2014
|Page(s)||750 - 769|
|Published online||22 October 2014|
Segmentation of the Poisson and negative binomial rate models: a penalized estimator
Revised: 16 December 2013
We consider the segmentation problem of Poisson and negative binomial (i.e. overdispersed Poisson) rate distributions. In segmentation, an important issue remains the choice of the number of segments. To this end, we propose a penalized -likelihood estimator where the penalty function is constructed in a non-asymptotic context following the works of L. Birgé and P. Massart. The resulting estimator is proved to satisfy an oracle inequality. The performances of our criterion is assessed using simulated and real datasets in the RNA-seq data analysis context.
Mathematics Subject Classification: 62G05 / 62G07 / 62P10
Key words: Distribution estimation / change-point detection / count data (RNA-seq) / poisson and negative binomial distributions / model selection
© EDP Sciences, SMAI 2014
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