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Advances in Statistics: Theory, Methodology, Applications and Data Analysis, 2nd...
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Advances in Statistics: Theory, Methodology, Applications and Data Analysis, 2nd Edition

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

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 3196

Special Issue Editor

Prof. Dr. Alicia Nieto-Reyes

E-Mail Website
Guest Editor
Department of Mathematics, Statistics and Computer Science, Universidad de Cantabria, 39005 Santander, Spain
Interests: statistical data depth; pattern recognition; ubiquitous computing; healthcare; functional data analysis; hypothesis testing; supervised classification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

The Special Issue is dedicated to exploring the latest advances in the Statistics area of Mathematics that are innovative in either their theoretical, methodological, or applicability approach. The potential topics of this Special Issue incorporate but are not limited to, non-parametric statistics; functional data analysis; fuzzy and random sets; multivariate statistics; classification: supervised and clustering, including machine learning techniques, robust statistics, hypothesis testing, and time series analysis.

Prof. Dr. Alicia Nieto-Reyes
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

  • non-parametric statistics
  • functional data analysis
  • fuzzy and random sets
  • multivariate statistics
  • classification

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Related Special Issue

Published Papers (2 papers)

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Research

7 pages, 246 KiB  
Communication
(Re-)Reading Sklar (1959)—A Personal View on Sklar’s Theorem
by Gery Geenens
Mathematics 2024, 12(3), 380; https://doi.org/10.3390/math12030380 - 24 Jan 2024
Cited by 1 | Viewed by 1722
Abstract
In this short communication, I share some personal thoughts on Sklar’s theorem and copulas after reading the original paper (Sklar, 1959) in French. After providing a literal translation of Sklar’s original statements, I argue that the modern version of ‘Sklar’s theorem’ given in [...] Read more.
In this short communication, I share some personal thoughts on Sklar’s theorem and copulas after reading the original paper (Sklar, 1959) in French. After providing a literal translation of Sklar’s original statements, I argue that the modern version of ‘Sklar’s theorem’ given in most references has a slightly different emphasis, which may lead to subtly different interpretations. In particular, with no reference to the subcopula, modern ‘Sklar’s theorem’ does not provide the clues to fully appreciate when the copula representation of a distribution may form a valid basis for dependence modelling and when it may not. Full article
(This article belongs to the Special Issue Advances in Statistics: Theory, Methodology, Applications and Data Analysis, 2nd Edition)
25 pages, 400 KiB  
Article
A Posterior p-Value for Homogeneity Testing of the Three-Sample Problem
by Yufan Wang and Xingzhong Xu
Mathematics 2023, 11(18), 3849; https://doi.org/10.3390/math11183849 - 8 Sep 2023
Viewed by 875
Abstract
In this paper, we study a special kind of finite mixture model. The sample drawn from the model consists of three parts. The first two parts are drawn from specified density functions, f1 and f2, while the third one is [...] Read more.
In this paper, we study a special kind of finite mixture model. The sample drawn from the model consists of three parts. The first two parts are drawn from specified density functions, f1 and f2, while the third one is drawn from the mixture. A problem of interest is whether the two functions, f1 and f2, are the same. To test this hypothesis, we first define the regular location and scale family of distributions and assume that f1 and f2 are regular density functions. Then the hypothesis transforms to the equalities of the location and scale parameters, respectively. To utilize the information in the sample, we use Bayes’ theorem to obtain the posterior distribution and give the sampling method. We then propose the posterior p-value to test the hypothesis. The simulation studies show that our posterior p-value largely improves the power in both normal and logistic cases and nicely controls the Type-I error. A real halibut dataset is used to illustrate the validity of our method. Full article
(This article belongs to the Special Issue Advances in Statistics: Theory, Methodology, Applications and Data Analysis, 2nd Edition)
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