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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

The family of skew-symmetric distributions is a wide set of probability density functions obtained by combining in a suitable form a few components which are selectable quite freely provided some simple requirements are satisfied. Intense…

Probability · Mathematics 2010-12-22 Adelchi Azzalini , Giuliana Regoli

The Mardia measures of multivariate skewness and kurtosis summarize the respective characteristics of a multivariate distribution with two numbers. However, these measures do not reflect the sub-dimensional features of the distribution.…

Methodology · Statistics 2022-07-20 Joydeep Chowdhury , Subhajit Dutta , Reinaldo B. Arellano-Valle , Marc G. Genton

In this note, we investigate the non-identifiability of the multivariate unified skew-normal distribution under permutation of its latent variables. We show that the non-identifiability issue also holds with other parametrizations and…

Statistics Theory · Mathematics 2023-06-23 Kesen Wang , Reinaldo B. Arellano-Valle , Adelchi Azzalini , Marc G. Genton

The unified skew-t (SUT) is a flexible parametric multivariate distribution that accounts for skewness and heavy tails in the data. A few of its properties can be found scattered in the literature or in a parameterization that does not…

Methodology · Statistics 2023-12-01 Kesen Wang , Maicon J. Karling , Reinaldo B. Arellano-Valle , Marc G. Genton

Since its introduction, the skew-$t$ distribution has received much attention in the literature both for the study of theoretical properties and as a model for data fitting in empirical work. A major motivation for this interest is the high…

Computation · Statistics 2019-07-25 Adelchi Azzalini , Mahdi Salehi

For the extended skew-normal distribution, which represents an extension of the normal (or Gaussian) distribution, we focus on the properties of the log-likelihood function and derived quantities in the the bivariate case. Specifically, we…

Statistics Theory · Mathematics 2023-09-20 Stefano Franco , Adelchi Azzalini

Azzalini & Dalla Valle (1996) have recently discussed the multivariate skew-normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further…

Methodology · Statistics 2009-11-12 Adelchi Azzalini , Antonella Capitanio

Distributions of strictly positive numbers are common and can be characterized by standard statistical measures such as mean, standard deviation, and skewness. We demonstrate that for these distributions the skewness $D_3$ is bounded from…

Applications · Statistics 2024-02-14 David J Meer , Eric R. Weeks

In this paper, a new mixture family of multivariate normal distributions, formed by mixing multivariate normal distribution and skewed distribution, is constructed. Some properties of this family, such as characteristic function, moment…

Methodology · Statistics 2020-09-24 Me'raj Abdi , Mohsen Madadi , N. Balakrishnan , Ahad Jamalizadeh

We introduce a new family of multivariate distributions by taking the component-wise Tukey-h transformation of a random vector following a skew-normal distribution. The proposed distribution is named the skew-normal-Tukey-h distribution and…

Methodology · Statistics 2023-10-19 Sagnik Mondal , Marc G. Genton

The multivariate extended skew-normal distribution allows for accommodating raw data which are skewed and heavy tailed, and has at least three appealing statistical properties, namely closure under conditioning, affine transformations, and…

Methodology · Statistics 2015-06-19 Mathieu Gerber , Florian Pelgrin

Motivated by the need for parametric families of rich and yet tractable distributions in financial mathematics, both in pricing and risk management settings, but also considering wider statistical applications, we investigate a novel…

Statistical Finance · Quantitative Finance 2009-01-06 William T. Shaw , Ian R. C. Buckley

The canonical form of scale mixtures of multivariate skew-normal distribution is defined, emphasizing its role in summarizing some key properties of this class of distributions. It is also shown that the canonical form corresponds to an…

Methodology · Statistics 2012-07-04 Antonella Capitanio

We propose a family of four-parameter distributions that contain the K-distribution as special case. The family is derived as a mixture distribution that uses the three-parameter reflected Gamma distribution as parental and the…

Statistics Theory · Mathematics 2021-07-09 Stylianos E. Trevlakis , Nestor D. Chatzidiamantis , George K. Karagiannidis

Kurtosis minus squared skewness is bounded from below by 1, but for unimodal distributions this parameter is bounded by 189/125. In some applications it is natural to compare distributions by comparing their kurtosis-minus-squared-skewness…

Statistics Theory · Mathematics 2023-12-12 Chris A. J. Klaassen , Bert van Es

The broad class of multivariate unified skew-normal (SUN) distributions has been recently shown to possess important conjugacy properties. When used as priors for the coefficients vector in probit, tobit, and multinomial probit models,…

Methodology · Statistics 2024-08-06 Maicon J. Karling , Daniele Durante , Marc G. Genton

This paper examines eight measures of skewness and Mardia measure of kurtosis for skew-elliptical distributions. Multivariate measures of skewness considered include Mardia, Malkovich-Afifi, Isogai, Song, Balakrishnan-Brito-Quiroz,…

Statistics Theory · Mathematics 2023-12-01 Baishuai Zuo , Narayanaswamy Balakrishnan , Chuancun Yin

In this paper we propose a family of multivariate asymmetric distributions over an arbitrary subset of set of real numbers which is defined in terms of the well-known elliptically symmetric distributions. We explore essential properties,…

Methodology · Statistics 2024-09-02 Roberto Vila , Helton Saulo , Leonardo Santos , João Monteiros , Felipe Quintino

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
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