Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.6
2.2
Journals
Mathematics
Special Issues
New Advance in Applied Probability and Statistical Inference
share announcement

New Advance in Applied Probability and Statistical Inference

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 467

Special Issue Editor

Dr. Maurizio Brizzi

E-Mail Website
Guest Editor
Department of Statistical Sciences, University of Bologna, 40126 Bologna, Italy
Interests: applied probability; quantile methods; fuzzy statistics; biometrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There is ever-increasing interest in the applications of probability and statistical inference, as the statistical view of thinking is spreading in almost every field. With the rapid advancements in data availability and computational tools, there is a growing need for innovative methods to address complex real-world problems.

This Special Issue aims to highlight recent developments in these areas, demonstrating how probability and statistical inference can be applied to a wide range of disciplines, both natural and social. We welcome contributions that explore novel applications and methodologies, showcasing how these tools can enhance our understanding of the world around us and improve decision-making processes in diverse fields.

Dr. Maurizio Brizzi
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 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

  • applied probability
  • discrete distributions
  • continuous models
  • statistical inference
  • point and interval estimation
  • quantile methods
  • fuzzy methods
  • parametric statistical tests
  • non-parametric statistical tests

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

22 pages, 487 KiB  
Article
Fuzzy Hypothesis Testing for Radar Detection: A Statistical Approach for Reducing False Alarm and Miss Probabilities
by Ahmed K. Elsherif, Hanan Haj Ahmad, Mohamed Aboshady and Basma Mostafa
Mathematics 2025, 13(14), 2299; https://doi.org/10.3390/math13142299 - 17 Jul 2025
Viewed by 326
Abstract
This paper addresses a fundamental challenge in statistical radar detection systems: optimizing the trade-off between the probability of a false alarm (PFA) and the probability of a miss (PM). These two metrics are inversely related and [...] Read more.
This paper addresses a fundamental challenge in statistical radar detection systems: optimizing the trade-off between the probability of a false alarm (PFA) and the probability of a miss (PM). These two metrics are inversely related and critical for performance evaluation. Traditional detection approaches often enhance one aspect at the expense of the other, limiting their practical applicability. To overcome this limitation, a fuzzy hypothesis testing framework is introduced that improves decision making under uncertainty by incorporating both crisp and fuzzy data representations. The methodology is divided into three phases. In the first phase, we reduce the probability of false alarm PFA while maintaining a constant probability of miss PM using crisp data characterized by deterministic values and classical statistical thresholds. In the second phase, the inverse scenario is considered: minimizing PM while keeping PFA fixed. This is achieved through parameter tuning and refined threshold calibration. In the third phase, a strategy is developed to simultaneously enhance both PFA and PM, despite their inverse correlation, by adopting adaptive decision rules. To further strengthen system adaptability, fuzzy data are introduced, which effectively model imprecision and ambiguity. This enhances robustness, particularly in scenarios where rapid and accurate classification is essential. The proposed methods are validated through both real and synthetic simulations of radar measurements, demonstrating their ability to enhance detection reliability across diverse conditions. The findings confirm the applicability of fuzzy hypothesis testing for modern radar systems in both civilian and military contexts, providing a statistically sound and operationally applicable approach for reducing detection errors and optimizing system performance. Full article
(This article belongs to the Special Issue New Advance in Applied Probability and Statistical Inference)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop