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In this paper we have introduced a generalized version of alpha beta skew normal distribution in the same line of Sharafi et al. (2017) and investigated some of its basic properties. The extensions of the proposed distribution have also…

Statistics Theory · Mathematics 2019-10-22 Sricharan Shah , Subrata Chakraborty , Partha Jyoti Hazarika , M. Masoom Ali

The family of multivariate skew-normal distributions has many interesting properties. It is shown here that these hold for a general class of skew-elliptical distributions. For this class, several stochastic representations are established…

Statistics Theory · Mathematics 2023-09-18 Chuancun Yin , Narayanaswamy Balakrishnan

Frequentist and likelihood methods of inference based on the multivariate skew-normal model encounter several technical difficulties with this model. In spite of the popularity of this class of densities, there are no broadly satisfactory…

Methodology · Statistics 2013-02-06 Brunero Liseo , Antonio Parisi

Finite mixture of skew distributions have emerged as an effective tool in modelling heterogeneous data with asymmetric features. With various proposals appearing rapidly in the recent years, which are similar but not identical, the…

Methodology · Statistics 2013-05-29 Sharon X. Lee , Geoffrey J. McLachlan

In this paper, we comment on the recent comparison in Azzalini et al. (2014) of two different distributions proposed in the literature for the modelling of data that have asymmetric and possibly long-tailed clusters. They are referred to as…

Methodology · Statistics 2014-04-08 Geoffrey J. McLachlan , Sharon X. Lee

Skewness is a common occurrence in statistical applications. In recent years, various distribution families have been proposed to model skewed data by introducing unequal scales based on the median or mode. However, we argue that the point…

Methodology · Statistics 2024-01-10 Yiyuan She , Xiaoqiang Wu , Lizhu Tao , Debajyoti Sinha

We examine some distributions used extensively within the model-based clustering literature in recent years, paying special attention to} claims that have been made about their relative efficacy. Theoretical arguments are provided as well…

Statistics Theory · Mathematics 2015-12-07 Adelchi Azzalini , Ryan P. Browne , Marc G. Genton , Paul D. McNicholas

Four new probability models are derived which generalize the common univariate continuous distributions. Classical distributional measures are derived from Hoel, et al., Introduction to Probability Theory, 1971. Measures include probability…

General Mathematics · Mathematics 2014-05-09 Francis J. O'Brien

Skew orthogonal polynomials arise in the calculation of the $n$-point distribution function for the eigenvalues of ensembles of random matrices with orthogonal or symplectic symmetry. In particular, the distribution functions are completely…

solv-int · Physics 2015-06-26 M. Adler , P. J. Forrester , T. Nagao , P. van Moerbeke

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

In this paper, we propose a new ellipsoidal mixture model. This model is based a new probability density function belonging to the family of elliptical distributions and designed to model points spread around an ellipsoidal surface. Then,…

Methodology · Statistics 2023-09-22 Denis Brazey , Antoine Godichon-Baggioni , Bruno Portier

Many approximate Bayesian inference methods assume a particular parametric form for approximating the posterior distribution. A multivariate Gaussian distribution provides a convenient density for such approaches; examples include the…

Methodology · Statistics 2023-02-20 Jackson Zhou , Clara Grazian , John Ormerod

In this paper we introduce a new lifetime distribution by compounding exponential and Poisson-Lindley distributions, named exponential Poisson-Lindley distribution. Several properties are derived, such as density, failure rate, mean…

Methodology · Statistics 2013-02-20 Wagner Barreto-Souza , Hassan S. Bakouch

This paper proposes a unified class of generalized location-scale mixture of multivariate elliptical distributions and studies integral stochastic orderings of random vectors following such distributions. Given a random vector…

Statistics Theory · Mathematics 2023-02-28 Tong Pu , Yiying Zhang , Chuancun Yin

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

We study Bayesian linear regression models with skew-symmetric scale mixtures of normal error distributions. These kinds of models can be used to capture departures from the usual assumption of normality of the errors in terms of heavy…

Applications · Statistics 2016-01-12 Francisco J. Rubio , Marc G. Genton

The challenges posed by complex stochastic models used in computational ecology, biology and genetics have stimulated the development of approximate approaches to statistical inference. Here we focus on Synthetic Likelihood (SL), a…

Methodology · Statistics 2017-06-09 Matteo Fasiolo , Simon N. Wood , Florian Hartig , Mark V. Bravington

In this paper, an alternative Discrete skew Logistic distribution is proposed, which is derived by using the general approach of discretizing a continuous distribution while retaining its survival function. The properties of the…

Methodology · Statistics 2016-04-07 Deepesh Bhati , Subrata Chakraborty , Snober Gowhar Lateef

A new class of distributions, called as normal power series (NPS), which contains the normal one as a particular case, is introduced in this paper. This new class which is obtained by compounding the normal and power series distributions,…

Methodology · Statistics 2015-10-27 Eisa Mahmoudi , Hamed Mahmoodian

The aim of this paper is to extend Azzalini's method. This extension is done in two stages: consider two dependent and non-identically distributed random variables say $X_1$ and $X_2$; model the dependence between $X_1$ and $X_2$ by a…

Statistics Theory · Mathematics 2018-03-06 Filippo Domma , Božidar V. Popović , Saralees Nadarajah