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.Stochastic models based on random diffusivities, such as the diffusing-diffusivity approach, are popular concepts for the description of non-Gaussian diffusion in heterogeneous media. Studies of these models typically focus on the moments…

Statistical Mechanics · Physics 2020-08-26 V. Sposini , D. S. Grebenkov , R. Metzler , G. Oshanin , F. Seno

The Weibull--like distributions form a large class of probability distributions that belong to the domain of attraction for the maxima of the Gumbel law. Besides the Weibull distribution, it includes important distributions as the Gamma…

Statistics Theory · Mathematics 2013-08-27 Armengol Gasull , José A. López-Salcedo , Frederic Utzet

A continuous approximation for the results of [1] is obtained. In this approximation the energy distribution is represented in the form of the product of the Gibbs factor and superstatistics factor. The mutual weights of the factors are…

Chemical Physics · Physics 2007-05-23 V. V. Ryazanov

We introduce a mixture of generalized hyperbolic distributions as an alternative to the ubiquitous mixture of Gaussian distributions as well as their near relatives of which the mixture of multivariate t and skew-t distributions are…

Methodology · Statistics 2017-10-09 Ryan P. Browne , Paul D. McNicholas

We present a simple method to quantitatively capture the heterogeneity in the degree distribution of a network graph using a single parameter $\sigma$. Using an exponential transformation of the shape parameter of the Weibull distribution,…

Data Analysis, Statistics and Probability · Physics 2023-05-05 Sinan A. Ozbay , Maximilian M. Nguyen

In this study an attempt has been made to propose a way to develop new distribution. For this purpose, we need only idea about distribution function. Some important statistical properties of the new distribution like moments, cumulants,…

Methodology · Statistics 2024-08-30 Brijesh P. Singh , Utpal Dhar Das

The Gumbel-Softmax probability distribution allows learning discrete tokens in generative learning, while the Gumbel-Argmax probability distribution is useful in learning discrete structures in discriminative learning. Despite the efforts…

Machine Learning · Computer Science 2024-06-05 Hedda Cohen Indelman , Tamir Hazan

In this paper, we propose a new class of bivariate distributions, called the bivariate discrete inverse Weibull (BDsIW) distribution, whose marginals are discrete inverse Weibull (DsIW) distributions. Some statistical and mathematical…

Statistics Theory · Mathematics 2018-08-24 M. S. Eliwa , M. El-Morshedy

In this paper, we introduce a generalized model for count data based upon an assumed Weibull interarrival process that nests the Poisson and negative binomial models as special cases. In addition, we demonstrate that this new Weibull count…

Methodology · Statistics 2021-07-21 Moshe Adrian , Eric Bradlow , Peter Fader , Blake McShane

Compound Poisson distributions have been employed by many authors to fit experimental data, typically via the method of moments or maximum likelihood estimation. We propose a new technique and apply it to several sets of published data. It…

Methodology · Statistics 2025-04-01 S. R. Mane

Bayesian spatial modeling of heavy-tailed distributions has become increasingly popular in various areas of science in recent decades. We propose a Weibull regression model with spatial random effects for analyzing extreme economic loss.…

Applications · Statistics 2019-12-10 Hou-Cheng Yang , Lijiang Geng , Yishu Xue , Guanyu Hu

In this article, we propose a new three parameter distribution by compounding negative binomial with reciprocal inverse Gaussian model called negative binomial-reciprocal inverse Gaussian distribution. This model is tractable with some…

Methodology · Statistics 2019-06-10 Ishfaq Shah Ahmad , Anwar Hassan , Peer Bilal Ahmad

Probabilistic models can be defined by an energy function, where the probability of each state is proportional to the exponential of the state's negative energy. This paper considers a generalization of energy-based models in which the…

Neurons and Cognition · Quantitative Biology 2016-05-25 Jan Humplik , Gašper Tkačik

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

A new three-parameter cumulative distribution function defined on $(\alpha,\infty)$, for some $\alpha\geq0$, with asymmetric probability density function and showing exponential decays at its both tails, is introduced. The new distribution…

Statistics Theory · Mathematics 2017-03-28 Meitner Cadena

In order to better fit real-world datasets, studying asymmetric distribution is of great interest. In this work, we derive several mathematical properties of a general class of asymmetric distributions with positive support which shows up…

Statistics Theory · Mathematics 2025-12-11 Felipe S. Quintino , Pushpa N. Rathie , Luan C. S. M. Ozelim , Tiago A. da Fonseca , Roberto Vila

The complex Gaussian distribution has been widely used as a fundamental spectral and noise model in signal processing and communication. However, its Gaussian structure often limits its ability to represent the diverse amplitude…

Machine Learning · Statistics 2026-03-30 Toru Nakashika

The aim of this paper, is to define a bivariate exponentiated generalized linear exponential distribution based on Marshall-Olkin shock model. Statistical and reliability properties of this distribution are discussed. This includes…

Statistics Theory · Mathematics 2017-10-03 Mohamed Ibrahim , M. S. Eliwa , M. El- Morshedy

In this paper we introduce a new flexible class of distributions with bounded support, called reflected Generalized Topp-Leone Power Series (rGTL-PS), obtained by compounding the reflected Generalized Topp-Leone (van Drop and Kotz, 2006)…

Methodology · Statistics 2016-07-20 Francesca Condino , Filippo Domma

The Weibull parametrization of the multiplicity distribution is used to describe the multidimensional local fluctuations and genuine multiparticle correlations measured by OPAL in the large statistics $e^{+}e^{-} \to Z^{0} \to hadrons$…

High Energy Physics - Phenomenology · Physics 2018-03-08 Ranjit K. Nayak , Sadhana Dash , Edward K. Sarkisyan-Grinbaum , Marek Tasevsky