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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

The maximum ${\log}_q$ likelihood estimation method is a generalization of the known maximum $\log$ likelihood method to overcome the problem for modeling non-identical observations (inliers and outliers). The parameter $q$ is a tuning…

Methodology · Statistics 2020-12-16 Mehmet Niyazi Çankaya , Roberto Vila

Hyperbolic space is increasingly used for hierarchical, tree-like, and network-structured data, but likelihood-based density modeling on hyperbolic space remains relatively limited. This paper develops finite mixture modeling with isotropic…

Methodology · Statistics 2026-04-29 Kisung You

In the present paper, Probability weighted moments (PWMs) method for parameter estimation of the median based unit weibull (MBUW) distribution is discussed. The most widely used first order PWMs is compared with the higher order PWMs for…

Methodology · Statistics 2025-11-20 Iman Mohammed Attia

Exponential random graph models (ERGMs) are widely used for modeling social networks observed at one point in time. However the computational difficulty of ERGM parameter estimation has limited the practical application of this class of…

Methodology · Statistics 2021-11-24 Alex Stivala , Garry Robins , Alessandro Lomi

The Weibull distribution can be obtained using a power transformation from the standard exponential distribution. In this article, we will consider a symmetrized power transformation of a random variable with the standard normal…

Probability · Mathematics 2024-01-09 Krzysztof Zajkowski

In this paper we study a wide and flexible family of discrete distributions, the so-called generalized negative binomial (GNB) distributions that are mixed Poisson distributions in which the mixing laws belong to the class of generalized…

Probability · Mathematics 2018-06-26 V. Yu. Korolev , A. I. Zeifman

An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness has received much attention in the model-based clustering literature recently, we investigate the use of a…

Methodology · Statistics 2015-06-15 Utkarsh J. Dang , Ryan P. Browne , Paul D. McNicholas

Sine-skewed circular distributions are identifiable and have easily-computable trigonometric moments and a simple random number generation algorithm, whereas they are known to have relatively low levels of asymmetry. This study proposes a…

Methodology · Statistics 2024-02-16 Yoichi Miyata , Takayuki Shiohama , Toshihiro Abe

The fracture strength distribution of materials is often described in terms of the Weibull law which can be derived by using extreme value statistics if elastic interactions are ignored. Here, we consider explicitly the interplay between…

Statistical Mechanics · Physics 2014-10-16 Zsolt Bertalan , Ashivni Shekhawat , James P. Sethna , Stefano Zapperi

The generalized gamma distribution shows up in many problems related to engineering, hydrology as well as survival analysis. Earlier work has been done that estimated the deviation of the exponential and the Weibull distribution from…

Probability · Mathematics 2022-11-10 Zelong Bi , Irfan Durmić , Steven J. Miller

In this article, a generalized inverse xgamma distribution (GIXGD) has been introduced as the generalized version of the inverse xgamma distribution. The proposed model exhibits the pattern of non-monotone hazard rate and belongs to family…

Methodology · Statistics 2018-12-13 Harsh Tripathi , Abhimanyu Singh Yadav , Mahendra Saha , Sumit Kumar

The projected normal distribution, also known as the angular Gaussian distribution, is obtained by dividing a multivariate normal random variable $\mathbf{x}$ by its norm $\sqrt{\mathbf{x}^T \mathbf{x}}$. The resulting random variable…

Methodology · Statistics 2025-06-24 Daniel Herrera-Esposito , Johannes Burge

The exponential random graph model (ERGM) is a central object in the study of clustering properties in social networks as well as canonical ensembles in statistical physics. Despite some breakthrough works in the mathematical understanding…

Probability · Mathematics 2021-08-06 Shirshendu Ganguly , Kyeongsik Nam

In this communication, we introduce a new statistical model and study its various mathematical properties. The expressions for hazard rate, reversed hazard rate, and odd functions are provided. We explore the asymptotic behaviors of the…

Methodology · Statistics 2023-04-24 Tuhin Subhra Mahatao , Subhankar Dutta , Suchandan Kayal

To account quantitatively for many reported ``natural'' fat tail distributions in Nature and Economy, we propose the stretched exponential family as a complement to the often used power law distributions. It has many advantages, among which…

Statistical Mechanics · Physics 2009-10-31 Jean Laherrère , D. Sornette

To examine the effect of exponential, Weibull and Gompertz distributions on sample size determination for superiority trials (STs) or non-inferiority trials (NTs) with time-to-event data, we present two sample size formulas for STs or NTs…

Applications · Statistics 2021-06-22 Dong Han , Yawen Hou , Zheng Chen

Extreme value distributions are routinely employed to assess risks connected to extreme events in a large number of applications. They typically are two- or three- parameter distributions: the inference can be unstable, which is…

Statistics Theory · Mathematics 2026-02-19 Nathan Huet , Ilaria Prosdocimi

The Gumbel model is a very popular statistical model due to its wide applicability for instance in the course of certain survival, environmental, financial or reliability studies. In this work, we have introduced a bimodal generalization of…

Methodology · Statistics 2021-06-22 Cira E. G. Otiniano , Roberto Vila , Pedro C. Brom , Marcelo Bourguignon

We introduce the weighted random graph (WRG) model, which represents the weighted counterpart of the Erdos-Renyi random graph and provides fundamental insights into more complicated weighted networks. We find analytically that the WRG is…

Statistical Mechanics · Physics 2016-09-08 Diego Garlaschelli