Skewed (Asymmetrical) Probability Distributions and Applications across Disciplines Fourth Edition

Dear Colleagues,

Skewed distributions are transversal and ubiquitous to all scientific disciplines. They have captured the attention of many researchers, as a deep understanding of their underlying probabilistic mechanisms is crucial in many fields. The right choice of the probability distribution for a non-normal stochastic process and the proper interpretation of its parameters can be very challenging and of enormous importance in fields such as physics, chemistry, biology, and social sciences.

The guidelines for contributions to this Special Issue include (but are not limited to) the following topics, which are divided into two broad groups:

• Methods and applications of skew distributions.
• New applications and parameter interpretations of the main skewed distributions;
• Parameter estimation and statistical developments;
• Advances in modelling and simulations (i.e., Monte Carlo sampling) of processes in mathematics, physics, chemistry, biology, and social sciences;
• Efficient numerical methods to handle skewed distributions;
• Skewed distributions and the modelling of infectious diseases, including COVID-19.

• Skewed distributions in describing natural processes.
• The true meaning of skewed distributions in nature;
• Skewed distributions in psychological and neurological sciences;
• Non-normal distributions in biological and medical sciences;
• Skewed distributions in describing social processes;
• The origin and fundamental interpretations of skewed distributions in mathematics, physics, chemistry, biology, and social sciences.

Prof. Dr. Juan Carlos Castro-Palacio
Prof. Dr. Pedro José Fernández de Córdoba Castellá
Prof. Dr. Shufei Wu
Dr. Miguel Enrique Iglesias Martínez
Guest Editors

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 submissions that pass pre-check are 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 2400 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.

• new applications and parameter interpretations of the main skewed distributions
• parameter estimation and statistical developments
• advances in modelling and simulations (i.e., Monte Carlo sampling) of processes in mathematics, physics, chemistry, biology, and social sciences
• efficient numerical methods to handle skewed distributions
• skewed distributions and the modelling of infectious diseases, including COVID-19
• the true meaning of skewed distributions in nature
• skewed distributions in psychological and neurological sciences
• non-normal distributions in biological and medical sciences
• skewed distributions in describing social processes
• the origin and fundamental interpretations of skewed distributions in mathematics, physics, chemistry, biology, and social sciences

• Skewed (Asymmetrical) Probability Distributions and Applications across Disciplines III in Symmetry (19 articles)

Title: A Simplified Discrete Model for Analyzing the Human Response Times to Visual Stimuli
Authors: Aina Noverques Medina; Marcos Orellana; José Guerra Carmenate; Miguel E. Iglesias Martínez; Juan Carlos Castro Palacio; Pedro Fernández de Córdoba.
Affiliation: Universitat Politècnica de València (UPV), Spain.
Abstract: In this paper, we streamline the model proposed in a previous study for representing the distribution of human response times to visual stimuli. We employ a Rayleigh distribution to depict the response time distribution within a group. Additionally, we introduce a discrete model to accurately compute the unique parameter B of the distribution. The obtained results quantitatively improve the previous work results considering the correlations values.

Title: Gumbel-Logistic Unit Distribution with Application in Telecommunications Data Modelling
Authors: Vladica S. Stojanović^1,a, Mihailo Jovanović^1,b, Brankica Pažun^2 and Zlatko Langović˘3
Affiliation: 1^Department of Informatics & Computer Sciences, University of Criminal Investigation and Police Studies, Belgrade, Serbia 2^Department of Informatics, Mathematics and Statistics, Faculty of Engineering Management, Belgrade, Serbia 3^Department of Business Economy, Faculty of Hotel Management and Tourism, University of Kragujevac, Vrnjačka Banja, Serbia
Abstract: The manuscript deals with a new two-parameter unit stochastic distribution, obtained by transforming the Gumbel distribution, using generalized logistic mapping, into a unit interval. The distribution obtained in this way is called the Gumbel-Logistic Unit (abbreviated GLU) distribution and its basic stochastic properties are examined in detail. Among others, it is shown that the GLU distribution, unlike the Gumbel one which is always positively asymmetric, can take both asymmetric forms. Also, the procedure for estimating parameters based on quantiles, along with the asymptotic properties of the obtained estimators and the study of their numerical simulation, is given. Finally, the application of the GLU distribution in modeling some real-world data related to telecommunications is discussed.