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Uncertainty Quantification Techniques in Statistics

This special issue belongs to the section “E: Applied Mathematics“.

Special Issue Information

Dear Colleagues,

Uncertainty Quantification (UQ) is a mainstream research topic in applied mathematics and statistics. To identify UQ problems, diverse modern techniques for large and complex data analysis have been developed in applied mathematics, computer science, and statistics.

To promote these modern data analysis methods in biology, economics, environmental studies, finance, mathematics, operational research, science, and statistics, a Special Issue of Mathematics (ISSN 2227-7390), the Science Citation Index Expanded (SCIE) Journal, will be devoted to “Uncertainty Quantification Techniques in Statistics”.

The Guest Editor for this Special Issue is Prof. Dr. Jong‐Min Kim.

Prof. Dr. Jong-Min Kim
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. 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

  • Bayesian statistics
  • Change-point detection
  • Computer model
  • Financial time series
  • Functional data analysis
  • Machine learning
  • Quality control
  • Spatial statistics

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