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A number of recent studies have estimated the inter-galactic void probability function and investigated its departure from various random models. We study a family of parametric statistical models based on gamma distributions, which do give…

Mathematical Physics · Physics 2008-11-27 C. T. J. Dodson

The current Poisson factor models often assume that the factors are unknown, which overlooks the explanatory potential of certain observable covariates. This study focuses on high dimensional settings, where the number of the count response…

Methodology · Statistics 2024-02-26 Wei Liu , Qingzhi Zhong

In this paper a new generalization of the hyper-Poisson distribution is proposed using the Mittag-Leffler function. The hyper-Poisson, displaced Poisson, Poisson and geometric distributions among others are seen as particular cases. This…

Statistics Theory · Mathematics 2014-11-05 Subrata Chakraborty , S. H. Ong

The problem of overdispersion in multivariate count data is a challenging issue. Nowadays, it covers a central role mainly due to the relevance of modern technologies data, such as Next Generation Sequencing and textual data from the web or…

Methodology · Statistics 2025-02-24 Noemi Corsini , Cinzia Viroli

We consider three new classes of exponential dispersion models of discrete probability distributions which are defined by specifying their variance functions in their mean value parameterization. In a previous paper (Bar-Lev and Ridder,…

Methodology · Statistics 2020-04-01 Shaul K. Bar-Lev , Ad Ridder

This article aims to introduced a new distribution named as extended xgamma (EXg) distribution. This generalization is derived from xgamma distribution (Xg), a special finite mixture of exponential and gamma distributions [see, Sen et al.…

Statistics Theory · Mathematics 2019-09-04 Mahendra Saha , Abhimanyu Singh Yadav , Arvind Pandey , Shivanshi Shukla , Sudhansu S Maiti

This paper introduces a novel family of geostatistical models designed to capture complex features beyond the reach of traditional Gaussian processes. The proposed family, termed the Poisson-Gaussian Mixture Process (POGAMP), is…

Methodology · Statistics 2024-12-09 F. B. Gonçalves , M. O. Prates , G. A. S. Aguilar

In this paper, we introduce a new generalization of geometric distribution which can also viewed as discrete analogue of weighted exponential distribution introduced by Gupta and Kundu(2009). We study some basic distributional properties…

Methodology · Statistics 2016-02-08 Deepesh Bhati , Savitri Joshi

This article presents a new class of generalized transmuted lifetime distributions which includes a large number of lifetime distributions as sub-family. Several important mathematical quantities such as density function, distribution…

Methodology · Statistics 2024-05-21 Alok Kumar Pandey , Alam Ali , Ashok Kumar Pathak

This paper presents a new derivation of the Generalized Poisson distribution. This distribution provides a good fit to the evolved, counts-in-cells distribution measured in numerical simulations of hierarchical clustering from Poisson…

Astrophysics · Physics 2009-10-30 Ravi K. Sheth

Transmuted geometric distribution (TGD) was recently introduced and investigated by Chakraborty and Bhati (2016). This is a flexible extension of geometric distribution having an additional parameter that determines its zero inflation as…

Methodology · Statistics 2016-10-25 Subrata Chakraborty , Deepesh Bhati

Bimodal truncated count distributions are frequently observed in aggregate survey data and in user ratings when respondents are mixed in their opinion. They also arise in censored count data, where the highest category might create an…

Methodology · Statistics 2014-01-24 Pragya Sur , Galit Shmueli , Smarajit Bose , Paromita Dubey

In this article we survey properties of mixed Poisson distributions and probabilistic aspects of the Stirling transform: given a non-negative random variable $X$ with moment sequence $(\mu_s)_{s\in\mathbb{N}}$ we determine a discrete random…

Combinatorics · Mathematics 2014-09-12 Markus Kuba , Alois Panholzer

The appropriateness of the Poisson model is frequently challenged when examining spatial count data marked by unbalanced distributions, over-dispersion, or under-dispersion. Moreover, traditional parametric models may inadequately capture…

Methodology · Statistics 2025-03-26 Mahsa Nadifar , Andriette Bekker , Mohammad Arashi , Abel Ramoelo

A new generalization of the family of Poisson-G is called beta Poisson-G family of distribution. Useful expansions of the probability density function and the cumulative distribution function of the proposed family are derived and seen as…

Statistics Theory · Mathematics 2020-05-22 Laba Handique , Subrata Chakraborty , Farrukh Jamal

Multivariate count data are commonly encountered through high-throughput sequencing technologies in bioinformatics, text mining, or in sports analytics. Although the Poisson distribution seems a natural fit to these count data, its…

Computation · Statistics 2020-04-16 Sanjeena Subedi , Ryan Browne

Event counts are response variables with non-negative integer values representing the number of times that an event occurs within a fixed domain such as a time interval, a geographical area or a cell of a contingency table. Analysis of…

The skewing mechanism of Azzalini for continuous distributions is used for the first time to derive a new generalization of the geometric distribution. Various structural properties of the proposed distribution are investigated.…

Statistics Theory · Mathematics 2020-10-12 Seng Huat Ong , Subrata Chakraborty , Aniket Biswas

Bayesian inference for models with intractable likelihood functions represents a challenging suite of problems in modern statistics. In this work we analyse the Conway-Maxwell-Poisson (COM-Poisson) distribution, a two parameter…

Computation · Statistics 2020-07-13 Alan Benson , Nial Friel

The Poisson distribution arises naturally when dealing with data involving counts, and it has found many applications in inverse problems and imaging. In this work, we develop an approximate Bayesian inference technique based on expectation…

Numerical Analysis · Mathematics 2019-09-04 Chen Zhang , Simon Arridge , Bangti Jin