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We propose a new method for estimating the extreme quantiles for a function of several dependent random variables. In contrast to the conventional approach based on extreme value theory, we do not impose the condition that the tail of the…

Methodology · Statistics 2013-11-25 Jinguo Gong , Yadong Li , Liang Peng , Qiwei Yao

In this paper, we discuss computational aspects to obtain accurate inferences for the parameters of the generalized gamma (GG) distribution. Usually, the solution of the maximum likelihood estimators (MLE) for the GG distribution have no…

Computation · Statistics 2017-07-26 Jorge Alberto Achcar , Pedro Luiz Ramos , Edson Zangiacomi Martinez

In this article we show the relationship between the Pareto distribution and the gamma distribution. This shows that the second one, appropriately extended, explains some anomalies that arise in the practical use of extreme value theory.…

Statistics Theory · Mathematics 2012-11-02 Joan del castillo , Jalila Daoudi , Isabel Serra

It has been shown that sufficiently well mixing dynamical systems with positive entropy have extreme value laws which in the limit converge to one of the three standard distributions known for i.i.d. processes, namely Gumbel, Fr\'echet and…

Probability · Mathematics 2015-08-05 Nicolai Haydn , Michal Kupsa

Heavy-tailed distributions are widely used in robust mixture modelling due to possessing thick tails. As a computationally tractable subclass of the stable distributions, sub-Gaussian $\alpha$-stable distribution received much interest in…

Machine Learning · Statistics 2017-01-25 Mahdi Teimouri , Saeid Rezakhah , Adel Mohammdpour

We introduce a general class of continuous univariate distributions with positive support obtained by transforming the class of two-piece distributions. We show that this class of distributions is very flexible, easy to implement, and…

Applications · Statistics 2015-11-06 Francisco J. Rubio , Yili Hong

Based on suitable left-truncated or censored data, two flexible classes of $M$-estimations of Weibull tail coefficient are proposed with two additional parameters bounding the impact of extreme contamination. Asymptotic normality with…

Statistics Theory · Mathematics 2018-10-18 Chengping Gong , Chengxiu Ling

Low-rank tensor models are widely used in statistics. However, most existing methods rely heavily on the assumption that data follows a sub-Gaussian distribution. To address the challenges associated with heavy-tailed distributions…

Methodology · Statistics 2025-09-16 Xiaoyu Zhang , Di Wang , Guodong Li , Defeng Sun

This paper provides an elementary, self-contained analysis of diffusion-based sampling methods for generative modeling. In contrast to existing approaches that rely on continuous-time processes and then discretize, our treatment works…

Machine Learning · Statistics 2025-06-25 Galen Reeves , Henry D. Pfister

Many events in biology are triggered when a diffusing searcher finds a target, which is called a first passage time (FPT). The overwhelming majority of FPT studies have analyzed the time it takes a single searcher to find a target. However,…

Probability · Mathematics 2020-10-23 Sean D Lawley

It is argued that there is a need for fat-tailed distributions that become thin in the extreme tail. A 3-parameter distribution is introduced that visually resembles the t-distribution and interpolates between the normal distribution and…

Statistics Theory · Mathematics 2022-02-08 Rose D Baker

The generalized negative binomial distribution (GNB) is a new flexible family of discrete distributions that are mixed Poisson laws with the mixing generalized gamma (GG) distributions. This family of discrete distributions is very wide and…

Methodology · Statistics 2018-09-18 Andrey K. Gorshenin , Victor Yu. Korolev

Reliability inference based on parametric distributions is an important problem in electrical and mechanical engineering. Most existing methods rely on approximations or bootstrap procedures, which may not perform satisfactorily when data…

Methodology · Statistics 2026-04-15 Bowen Liu , Malwane M. A. Ananda , Sam Weerahandi

The approximation of a discrete probability distribution $\mathbf{t}$ by an $M$-type distribution $\mathbf{p}$ is considered. The approximation error is measured by the informational divergence $\mathbb{D}(\mathbf{t}\Vert\mathbf{p})$, which…

Information Theory · Computer Science 2016-07-28 Bernhard C. Geiger , Georg Böcherer

We use extreme value theory to estimate the probability of successive exceedances of a threshold value of a time-series of an observable on several classes of chaotic dynamical systems. The observables have either a Fr\'echet (fat-tailed)…

Dynamical Systems · Mathematics 2023-11-07 Meagan Carney , Mark Holland , Matthew Nicol , Phuong Tran

Triangular distributions are a well-known class of distributions that are often used as an elementary example of a probability model. Maximum likelihood estimation of the mode parameter of the triangular distribution over the unit interval…

Other Statistics · Statistics 2016-11-08 Hien D Nguyen , Geoffrey J McLachlan

Maximum-type statistics of certain functions of the sample covariance matrix of high-dimensional vector time series are studied to statistically confirm or reject the null hypothesis that a data set has been collected under normal…

Statistics Theory · Mathematics 2023-10-13 Ansgar Steland

We give the distribution of $M_n$, the maximum of a sequence of $n$ observations from a moving average of order 1. Solutions are first given in terms of repeated integrals and then for the case where the underlying independent random…

Methodology · Statistics 2009-04-06 Christopher S. Withers , Saralees Nadarajah

In this paper we propose a new lifetime model, called the odd generalized exponential linear failure rate distribution. Some statistical properties of the proposed distribution such as the moments, the quantiles, the median, and the mode…

Statistics Theory · Mathematics 2015-10-28 M. A. El-Damcese , Abdelfattah Mustafa , B. S. El-Desouky , M. E. Mustafa

In this paper, we introduce a bivariate exponentaited generalized Weibull-Gompertz distribution. The model introduced here is of Marshall-Olkin type. Several properties are studied such as bivariate probability density function and it is…

Statistics Theory · Mathematics 2015-01-19 M. A. EL-Damcese , Abdelfattah Mustafa , M. S. Eliwa