Probability, Statistics & Symmetry, 2nd edition
A special issue of Mathematics (ISSN 2227-7390).
Deadline for manuscript submissions: 30 April 2026 | Viewed by 6
Special Issue Editors
Interests: survival analysis; regression analysis; theory of distributions; bias reduction methodologies; EM-type algorithms
Special Issues, Collections and Topics in MDPI journals
Interests: statistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Symmetry is a fundamental concept in statistics and probability, with broad theoretical and practical implications. Its presence naturally emerges across a wide range of applied disciplines, including engineering, medicine, psychology, economics, and many other fields of knowledge. Symmetry, along with its counterpart, asymmetry, plays a crucial role in the formulation of statistical models, the interpretation of data, and the development of more accurate and robust inference methods.
This Special Issue aims to gather original contributions that present new theoretical developments, computational advances, or innovative applications related to symmetry and asymmetry in statistics and probability. Authors are invited to submit research that explores how these concepts can be leveraged to address current challenges, enhance data analysis, or enrich the existing theoretical framework. In particular, studies that build bridges between mathematical theory and practical applications are especially encouraged, as well as those that propose novel methodological approaches or effective computational tools.
Through this initiative, we seek to foster the exchange of ideas among researchers from various fields, promoting an integrative perspective that highlights the relevance of symmetry as a unifying structural principle in contemporary statistical and probabilistic analysis.
The scope includes, but is not limited to, the following topics:
- Distribution theory;
- Regression models;
- Survival analysis;
- Inference based on entropy;
- K-record values;
- Inference in stochastic processes;
- Machine learning;
- Time series analysis.
Dr. Diego I. Gallardo
Dr. Marcelo Bourguignon
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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
- distribution theory
- distribution theory
- regression models
- survival analysis
- inference based on entropy
- K-record values
- inference in stochastic processes
- machine learning
- time series analysis
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