Compound Poisson point processes, concentration and oracle inequalities

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Abstract

This note aims at presenting several new theoretical results for the compound Poisson point process, which follows the work of Zhang et al. (Insur. Math. Econ. 59:325–336, 2014). The first part provides a new characterization for a discrete compound Poisson point process (proposed by Aczél (Acta Math. Hung. 3(3):219–224, 1952)), it extends the characterization of the Poisson point process given by Copeland and Regan (Ann. Math. 37:357–362, 1936). Next, we derive some concentration inequalities for discrete compound Poisson point process (negative binomial random variable with unknown dispersion is a significant example). These concentration inequalities are potentially useful in count data regression. We give an application in the weighted Lasso penalized negative binomial regressions whose KKT conditions of penalized likelihood hold with high probability and then we derive non-asymptotic oracle inequalities for a weighted Lasso estimator.

Original languageEnglish
Article number312
JournalJournal of Inequalities and Applications
Volume2019
Issue number1
DOIs
StatePublished - 2019
Externally publishedYes

Keywords

  • Characterization of point processes
  • Concentration inequalities
  • High-dimensional negative binomial regressions
  • Poisson random measure
  • Sub-gamma random variables

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