This paper gives a review of concentration inequalities which are widely employed in non-
asymptotical analyses of mathematical statistics in a wide range of settings, from distribution …

The distribution of insurance losses has a positive support and is often unimodal hump-
shaped, right-skewed and with heavy tails. In this work, we introduce a 3-parameter …

Stata has several procedures that can be used in analyzing count-data regression models
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A quasi-infinitely divisible distribution on $\mathbb {R} $ is a probability distribution whose
characteristic function allows a Lévy–Khintchine type representation with a “signed Lévy …

We study a sparse negative binomial regression (NBR) for count data by showing the non-
asymptotic advantages of using the elastic-net estimator. Two types of oracle inequalities …

Common count distributions, such as the Poisson (binomial) distribution for unbounded
(bounded) counts considered here, can be characterized by appropriate Stein identities …

The aim of this paper is to give some new characterizations of discrete compound Poisson
distributions. Firstly, we give a characterization by the Lévy–Khintchine formula of infinitely …

We consider discrete probability laws on the real line, whose characteristic functions are
separated from zero. This class includes arbitrary discrete infinitely divisible laws and lattice …

Modelling edge weights play a crucial role in the analysis of network data, which reveals the
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