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Bayesian inversion generates a posterior distribution of model parameters from an observation equation and prior information both weighted by hyperparameters. The prior is also introduced for the hyperparameters in fully Bayesian inversions…

Geophysics · Physics 2022-07-20 Dye SK Sato , Yukitoshi Fukahata , Yohei Nozue

The aim of this article is to determine a new six-parameter Beta Weibull distribution and its various associated functions, namely the cumulative distribution, survival, probability density and hazard functions. Next, we determine the…

Statistics Theory · Mathematics 2026-04-07 Didier Alain Njamen Njomen , Fidel Djongreba Ndikwa

The skew-normal and the skew-$t$ distributions are parametric families which are currently under intense investigation since they provide a more flexible formulation compared to the classical normal and $t$ distributions by introducing a…

Methodology · Statistics 2012-03-13 Adelchi Azzalini , Reinaldo B. Arellano-Valle

In this paper, we extend Beta distribution to 2 by 2 matrix and give the analytical formula for its moments. Our analytical formula can be used to analyze the asymptotic behavior of Beta distribution for 2 by 2 matrix.

Applications · Statistics 2020-09-15 Feng Zhao

Recently, Lee and Cha (2015, `On two generalized classes of discrete bivariate distributions', {\it American Statistician}, 221 - 230) proposed two general classes of discrete bivariate distributions. They have discussed some general…

Methodology · Statistics 2018-05-01 Debasis Kundu , Vahid Nekoukhou

Understanding variable dependence, particularly eliciting their statistical properties given a set of covariates, provides the mathematical foundation in practical operations management such as risk analysis and decision-making given…

Methodology · Statistics 2023-09-06 Yunyun Wang , Tatsushi Oka , Dan Zhu

In this paper, a new natural discrete version of the one parameter polynomial exponential family of distributions have been proposed and studied. The distribution is named as Natural Discrete One Parameter Polynomial Exponential (NDOPPE)…

Statistics Theory · Mathematics 2020-07-08 Sudhansu S. Maiti , Molay Kumar Ruidas , Sumanta Adhya

The most well known probability distribution of probabilities is the Beta distribution. If we have observed $r$ `successes', each having a probability $\theta$, and $n-r$ `failures', each having a probability $1-\theta$. In this paper we…

Methodology · Statistics 2015-03-04 H. R. N. van Erp , R. O. Linger , P. H. A. J. M. van Gelder

This paper presents foundational theoretical results on distributed parameter estimation for undirected probabilistic graphical models. It introduces a general condition on composite likelihood decompositions of these models which…

Machine Learning · Statistics 2014-06-13 Yariv Dror Mizrahi , Misha Denil , Nando de Freitas

In this paper, we introduce a new distribution called Burr III-Weibull(BW) distribution using the concept of competing risk. We derive moments, conditional moments, mean deviation and quantiles of the proposed distribution. Also the Renyi's…

Statistics Theory · Mathematics 2021-03-08 G S Deepthy , Nicy Sebastian , Reshma Rison

In this paper, we introduce a new extension of the generalized linear failure rate distributions. It includes some well-known lifetime distributions such as extension of generalized exponential and generalized linear failure rate…

Statistics Theory · Mathematics 2016-03-10 Mohammad Reza Kazemi , Ali Akbar Jafari , Saeid Tahmasebi

In this paper we develop a bivariate discrete generalized exponential distribution, whose marginals are discrete generalized exponential distribution as proposed by Nekoukhou, Alamatsaz and Bidram ("Discrete generalized exponential…

Methodology · Statistics 2017-01-16 Vahid Nekoukhou , Debasis Kundu

We introduce negative binomial matrix factorization (NBMF), a matrix factorization technique specially designed for analyzing over-dispersed count data. It can be viewed as an extension of Poisson matrix factorization (PF) perturbed by a…

Machine Learning · Computer Science 2018-01-08 Olivier Gouvert , Thomas Oberlin , Cédric Févotte

In this paper we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy…

Methodology · Statistics 2020-05-08 R. Vila , L. Ferreira , H. Saulo , F. Prataviera , E. M. M. Ortega

Method of parameterizing and smoothing the unknown underling distributions using Bernstein polynomials is proposed, verified and investigated. Any distribution with bounded and smooth enough density can be approximated by the proposed…

Methodology · Statistics 2015-06-23 Zhong Guan

In this paper, we introduce a new distribution generated by Lindley random variable which offers a more flexible model for modelling lifetime data. Various statistical properties like distribution function, survival function, moments,…

Applications · Statistics 2016-11-25 Deepesh Bhati , Mohd. Aamir Malik

Some special functions are particularly relevant in applied probability and statistics. For example, the incomplete beta function is the cumulative central beta distribution. In this paper, we consider the inversion of the central…

Classical Analysis and ODEs · Mathematics 2020-12-18 Amparo Gil , Javier Segura , Nico M. Temme

Categorical random variables are a common staple in machine learning methods and other applications across disciplines. Many times, correlation within categorical predictors exists, and has been noted to have an effect on various algorithm…

Probability · Mathematics 2017-01-25 Rachel Traylor

This work presents a construction of stationary Markov models with negative-binomial marginal distributions. A simple closed form expression for the corresponding transition probabilities is given, linking the proposal to well-known classes…

Methodology · Statistics 2019-04-10 Fabrizio Leisen , Ramsés H. Mena , Freddy Palma Mancilla , Luca Rossini

We investigate stochastic comparisons between exponential family distributions and their mixtures with respect to the usual stochastic order, the hazard rate order, the reversed hazard rate order, and the likelihood ratio order. A general…

Statistics Theory · Mathematics 2009-10-05 Yaming Yu