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Multivariate Statistics and Applications

Special Issue Information

Dear Colleagues,

I am pleased to announce a Special Issue on Multivariate Statistics and Applications. Being that nature is multivariate, it is not surprising that a phenomenon would usually depend on several factors, possibly correlated and whose representation must necessarily involve a useful methodology able to understand and process information in a meaningful fashion. The ambitious aim of this Special Issue is to present a wide range of the newest results on multivariate statistical models, distribution theory, and applications of multivariate statistical methods where applications range from finance and insurance mathematics to medical and industrial statistics and sampling algorithms. Multivariate statistical methods are also essential in communication research and in the developing process of models for online monitoring and control. Copula-based models able to deal with tail dependences of variables are particularly suited to representing special phenomena where natural variables such as wind, air pressure, temperature, and seasonal variations linked to the impact of climate change are involved. Similarly, manuscripts putting forward specific multivariate statistics methodologies which can be useful to practitioners are highly appreciated.

I look forward to receiving your submissions.

Dr. Silvia Romagnoli
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 250 words) can be sent to the Editorial Office for assessment.

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. Stats 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 1600 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

  • Copula function
  • Principal component analysis
  • Clustering systems
  • Artificial neural network
  • Factor Analysis

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Stats - ISSN 2571-905X