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Contemporary Bayesian Analysis: Methods and Applications

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue in the journal Mathematics of MDPI on “Contemporary Bayesian Analysis: Methods and Applications”. This Special Issue recognizes the Bayesian revolution in econometrics, statistics, and data science, especially pertaining to their methods and applications.

Authors with papers using any Bayesian approaches are encouraged to submit their papers or have a discussion with us. Papers with recent methods and applications are more than welcome. We also expect to receive contributions from emerging researchers.

Best regards,

Dr. Nuttanan Wichitaksorn
Dr. Mengheng Li
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

  • Bayesian analysis
  • econometrics and statistics
  • time series analysis and forecasting
  • Bayesian applications
  • Bayesian machine learning

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Published Papers