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The skew normal law has been introduced in Azzalin (1985) as an alternative to adjusting asymmetric data that share important patterns with the normal law. It has been extensively studied. However, there is so much to do in order to catch…

Methodology · Statistics 2025-07-25 Diam Ba , Gorgui Gning , Gandasor Bonyiri Onesiphore Da , Oumar Foly Sow , Gane Samb Lo

Some remarkable properties of the beta distribution are based on relations involving independence between beta random variables such that a parameter of one among them is the sum of the parameters of an other (see (1.1) et (1.2) below).…

Probability · Mathematics 2013-02-15 Abdelhamid Hassairi , Mouna Masmoudi

The shortcomings of the traditional univariate distributions in the past greatly encouraged mathematical statisticians to develop new generalizations of distributions. The New Generalized Fisk distribution, a unique distribution presented…

Methodology · Statistics 2025-04-22 Veeranna Banoth

The Akaike information criterion (AIC) is a common tool for model selection. It is frequently used in violation of regularity conditions at parameter space singularities and boundaries. The expected AIC is generally not asymptotically…

Statistics Theory · Mathematics 2022-11-09 Jonathan D. Mitchell , Elizabeth S. Allman , John A. Rhodes

In this paper we have proposed a model for the distribution of allelic probabilities for generating populations as reliably as possible. Our objective was to develop such a model which would allow simulating allelic probabilities with…

Motivated by the analysis of the distribution of university grades, which is usually asymmetric, we discuss two informative priors for the shape parameter of the skew-normal distribution, showing that they lead to closed-form…

Methodology · Statistics 2013-05-15 Antonio Canale , Bruno Scarpa

In bayesian wavelet shrinkage, the already proposed priors to wavelet coefficients are assumed to be symmetric around zero. Although this assumption is reasonable in many applications, it is not general. The present paper proposes the use…

Methodology · Statistics 2020-10-12 Alex Rodrigo dos Santos Sousa

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 contribution of this work is the introduction of a multivariate circular-linear (or poly- cylindrical) distribution obtained by combining the projected and the skew-normal. We show the flexibility of our proposal, its property of…

Methodology · Statistics 2017-11-29 Gianluca Mastrantonio

With the progress of information technology, large amounts of asymmetric, leptokurtic and heavy-tailed data are arising in various fields, such as finance, engineering, genetics and medicine. It is very challenging to model those kinds of…

Methodology · Statistics 2024-01-26 Chengdi Lian , Yaohua Rong , Weihu Cheng

We study the expectations of some ratio-type estimators under the gamma distribution. Expectations of ratio-type estimators are often difficult to compute due to the nature that they are constructed by combining two separate estimators.…

Statistics Theory · Mathematics 2025-05-09 Jia-Han Shih

We introduce the beta generalized exponential distribution that includes the beta exponential and generalized exponential distributions as special cases. We provide a comprehensive mathematical treatment of this distribution. We derive the…

Methodology · Statistics 2010-08-17 Wagner Barreto-Souza , Alessandro H. S. Santos , Gauss M. Cordeiro

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

We study with some details a lifetime model of the class of beta generalized models, called the beta inverse Rayleigh distribution, which is a special case of the Beta Fr\'echet distribution. We provide a better foundation for some…

Statistics Theory · Mathematics 2022-06-06 J. Leão , H. Saulo , M. Bourguignon , R. J. Cintra , L. C. Rêgo , G. M. Cordeiro

The skewing mechanism of Azzalini for continuous distributions is used for the first time to derive a new generalization of the geometric distribution. Various structural properties of the proposed distribution are investigated.…

Statistics Theory · Mathematics 2020-10-12 Seng Huat Ong , Subrata Chakraborty , Aniket Biswas

Fisheries scientists use regression models to estimate population quantities, such as biomass or abundance, for use in climate, habitat, stock, and ecosystem assessments. However, these models are sensitive to the chosen probability…

Methodology · Statistics 2025-01-13 Jillian C. Dunic , Jason Conner , Sean C. Anderson , James T. Thorson

In this article, a generalized version of Negative binomial-beta exponential distribution with five parameters have been introduced. Some interesting submodels have been derived from it. A comprehensive mathematical treatment of proposed…

Statistics Theory · Mathematics 2019-05-31 Anwar Hassan , Ishfaq Shah Ahmad , Peer Bilal Ahmad

Two approaches are suggested to the definition of asymmetric generalized Weibull distribution. These approaches are based on the representation of the two-sided Weibull distributions as variance-mean normal mixtures or more general…

Probability · Mathematics 2015-06-23 Victor Korolev , Lily Kurmangazieva , Alexander Zeifman

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

Normality is the most often mathematical supposition used in data modeling. Nonetheless, even based on the law of large numbers (LLN), normality is a strong presumption given that the presence of asymmetry and multi-modality in real-world…