Special Issue "Symmetric and Asymmetric Distributions: Theoretical Developments and Applications"

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: closed (30 September 2019).

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A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Emilio Gómez Déniz
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Guest Editor
Department of Quantitative Methods and TIDES Institute, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017-Las Palmas de Gran Canaria, Spain
Interests: Distributions Theory; Bayesian Statistics; Robustness; Bayesian Applications in Economics (Actuarial, Credibility, Ruin Theory)
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Special Issue Information

Dear Colleagues,

In recent decades, the number of theoretical and applied statistical works related to symmetric distributions has proliferated; the majority of these works are based on the Azzalini's scheme. This strategy uses a symmetric distribution as baseline, then a parameter is added to the standard model that controls the asymmetry of the new family of probability distributions. The most widespread and popular model is the one based on the normal distribution that gives rise to the skew normal distribution.

In this Special Issue on symmetrical distributions, researchers are invited to contribute original research papers and case studies related to this topic. Submissions that extend the Azzalini's scheme or propose alternatives, both for univariate and multivariate, continuous and discrete distributions are welcome. Researchers are also invited to offer theoretical and applied proposals that have connection with this subject. Applications in the fields of economics (inflation forecasting, stochastic frontier models, insurance, etc.), environmental sciences (climate changes, for instance), biometrics, engineering (reliability, classification of satellite image, etc.), and others fields are welcome.

This Special Issue is open to both original research articles and review articles, both theoretical and applied, within the area of symmetric and asymmetric distributions.

Prof. Dr. Emilio Gómez-Déniz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Applications
  • Bayesian
  • Kurtosis
  • Order Statistics
  • Simulation
  • Skewness

Published Papers (9 papers)

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Research

Open AccessArticle
Modified Power-Symmetric Distribution
Symmetry 2019, 11(11), 1410; https://doi.org/10.3390/sym11111410 - 15 Nov 2019
Cited by 3
Abstract
In this paper, a general class of modified power-symmetric distributions is introduced. By choosing as symmetric model the normal distribution, the modified power-normal distribution is obtained. For the latter model, some of its more relevant statistical properties are examined. Parameters estimation is carried [...] Read more.
In this paper, a general class of modified power-symmetric distributions is introduced. By choosing as symmetric model the normal distribution, the modified power-normal distribution is obtained. For the latter model, some of its more relevant statistical properties are examined. Parameters estimation is carried out by using the method of moments and maximum likelihood estimation. A simulation analysis is accomplished to study the performance of the maximum likelihood estimators. Finally, we compare the efficiency of the modified power-normal distribution with other existing distributions in the literature by using a real dataset. Full article
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Open AccessArticle
Normal-G Class of Probability Distributions: Properties and Applications
Symmetry 2019, 11(11), 1407; https://doi.org/10.3390/sym11111407 - 15 Nov 2019
Cited by 2
Abstract
In this paper, we propose a novel class of probability distributions called Normal-G. It has the advantage of demanding no additional parameters besides those of the parent distribution, thereby providing parsimonious models. Furthermore, the class enjoys the property of identifiability whenever [...] Read more.
In this paper, we propose a novel class of probability distributions called Normal-G. It has the advantage of demanding no additional parameters besides those of the parent distribution, thereby providing parsimonious models. Furthermore, the class enjoys the property of identifiability whenever the baseline is identifiable. We present special Normal-G sub-models, which can fit asymmetrical data with either positive or negative skew. Other important mathematical properties are described, such as the series expansion of the probability density function (pdf), which is used to derive expressions for the moments and the moment generating function (mgf). We bring Monte Carlo simulation studies to investigate the behavior of the maximum likelihood estimates (MLEs) of two distributions generated by the class and we also present applications to real datasets to illustrate its usefulness. Full article
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Open AccessArticle
Generalized Truncation Positive Normal Distribution
Symmetry 2019, 11(11), 1361; https://doi.org/10.3390/sym11111361 - 03 Nov 2019
Abstract
In this article we study the properties, inference, and statistical applications to a parametric generalization of the truncation positive normal distribution, introducing a new parameter so as to increase the flexibility of the new model. For certain combinations of parameters, the model includes [...] Read more.
In this article we study the properties, inference, and statistical applications to a parametric generalization of the truncation positive normal distribution, introducing a new parameter so as to increase the flexibility of the new model. For certain combinations of parameters, the model includes both symmetric and asymmetric shapes. We study the model’s basic properties, maximum likelihood estimators and Fisher information matrix. Finally, we apply it to two real data sets to show the model’s good performance compared to other models with positive support: the first, related to the height of the drum of the roller and the second, related to daily cholesterol consumption. Full article
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Open AccessArticle
Skewness of Maximum Likelihood Estimators in the Weibull Censored Data
Symmetry 2019, 11(11), 1351; https://doi.org/10.3390/sym11111351 - 01 Nov 2019
Cited by 2
Abstract
In this paper, we obtain a matrix formula of order n 1 / 2 , where n is the sample size, for the skewness coefficient of the distribution of the maximum likelihood estimators in the Weibull censored data. The present result is [...] Read more.
In this paper, we obtain a matrix formula of order n 1 / 2 , where n is the sample size, for the skewness coefficient of the distribution of the maximum likelihood estimators in the Weibull censored data. The present result is a nice approach to verify if the assumption of the normality of the regression parameter distribution is satisfied. Also, the expression derived is simple, as one only has to define a few matrices. We conduct an extensive Monte Carlo study to illustrate the behavior of the skewness coefficient and we apply it in two real datasets. Full article
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Open AccessArticle
Flexible Birnbaum–Saunders Distribution
Symmetry 2019, 11(10), 1305; https://doi.org/10.3390/sym11101305 - 16 Oct 2019
Cited by 2
Abstract
In this paper, we propose a bimodal extension of the Birnbaum–Saunders model by including an extra parameter. This new model is termed flexible Birnbaum–Saunders (FBS) and includes the ordinary Birnbaum–Saunders (BS) and the skew Birnbaum–Saunders (SBS) model as special cases. Its properties are [...] Read more.
In this paper, we propose a bimodal extension of the Birnbaum–Saunders model by including an extra parameter. This new model is termed flexible Birnbaum–Saunders (FBS) and includes the ordinary Birnbaum–Saunders (BS) and the skew Birnbaum–Saunders (SBS) model as special cases. Its properties are studied. Parameter estimation is considered via an iterative maximum likelihood approach. Two real applications, of interest in environmental sciences, are included, which reveal that our proposal can perform better than other competing models. Full article
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Open AccessArticle
An Asymmetric Distribution with Heavy Tails and Its Expectation–Maximization (EM) Algorithm Implementation
Symmetry 2019, 11(9), 1150; https://doi.org/10.3390/sym11091150 - 10 Sep 2019
Cited by 1
Abstract
In this paper we introduce a new distribution constructed on the basis of the quotient of two independent random variables whose distributions are the half-normal distribution and a power of the exponential distribution with parameter 2 respectively. The result is a distribution with [...] Read more.
In this paper we introduce a new distribution constructed on the basis of the quotient of two independent random variables whose distributions are the half-normal distribution and a power of the exponential distribution with parameter 2 respectively. The result is a distribution with greater kurtosis than the well known half-normal and slashed half-normal distributions. We studied the general density function of this distribution, with some of its properties, moments, and its coefficients of asymmetry and kurtosis. We developed the expectation–maximization algorithm and present a simulation study. We calculated the moment and maximum likelihood estimators and present three illustrations in real data sets to show the flexibility of the new model. Full article
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Open AccessArticle
An Asymmetric Bimodal Distribution with Application to Quantile Regression
Symmetry 2019, 11(7), 899; https://doi.org/10.3390/sym11070899 - 10 Jul 2019
Cited by 1
Abstract
In this article, we study an extension of the sinh Cauchy model in order to obtain asymmetric bimodality. The behavior of the distribution may be either unimodal or bimodal. We calculate its cumulative distribution function and use it to carry out quantile regression. [...] Read more.
In this article, we study an extension of the sinh Cauchy model in order to obtain asymmetric bimodality. The behavior of the distribution may be either unimodal or bimodal. We calculate its cumulative distribution function and use it to carry out quantile regression. We calculate the maximum likelihood estimators and carry out a simulation study. Two applications are analyzed based on real data to illustrate the flexibility of the distribution for modeling unimodal and bimodal data. Full article
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Open AccessArticle
Univariate and Bivariate Models Related to the Generalized Epsilon–Skew–Cauchy Distribution
Symmetry 2019, 11(6), 794; https://doi.org/10.3390/sym11060794 - 14 Jun 2019
Cited by 2
Abstract
In this paper, we consider a stochastic representation of the epsilon–skew–Cauchy distribution, viewed as a member of the family of skewed distributions discussed in Arellano-Valle et al. (2005). The stochastic representation facilitates derivation of distributional properties of the model. In addition, we introduce [...] Read more.
In this paper, we consider a stochastic representation of the epsilon–skew–Cauchy distribution, viewed as a member of the family of skewed distributions discussed in Arellano-Valle et al. (2005). The stochastic representation facilitates derivation of distributional properties of the model. In addition, we introduce symmetric and asymmetric extensions of the Cauchy distribution, together with an extension of the epsilon–skew–Cauchy distribution. Multivariate versions of these distributions can be envisioned. Bivariate examples are discussed in some detail. Full article
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Open AccessArticle
A Note on Ordering Probability Distributions by Skewness
Symmetry 2018, 10(7), 286; https://doi.org/10.3390/sym10070286 - 16 Jul 2018
Abstract
This paper describes a complementary tool for fitting probabilistic distributions in data analysis. First, we examine the well known bivariate index of skewness and the aggregate skewness function, and then introduce orderings of the skewness of probability distributions. Using an example, we highlight [...] Read more.
This paper describes a complementary tool for fitting probabilistic distributions in data analysis. First, we examine the well known bivariate index of skewness and the aggregate skewness function, and then introduce orderings of the skewness of probability distributions. Using an example, we highlight the advantages of this approach and then present results for these orderings in common uniparametric families of continuous distributions, showing that the orderings are well suited to the intuitive conception of skewness and, moreover, that the skewness can be controlled via the parameter values. Full article
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