Bayesian Statistical Methods for Forecasting
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 300
Special Issue Editors
Interests: statistical modeling; Bayesian inference; prediction; computational statistical methods; mixture models
Special Issue Information
Dear Colleagues,
In many statistical modeling problems, the main interest is to fit a model that explains the observed data well and can provide accurate predictions. In this context, Bayesian inference emerges as a very interesting option because its probabilistic framework allows for the obtainment of a prediction distribution that describes the uncertainty associated with future outcomes. This interesting characteristic of the Bayesian approach, together with the increasing availability of computational resources, has made the use of Bayesian methods for forecasting more accessible and applicable to forecasting problems from all fields of science. The idea of this Special Issue is to publish a collection of articles in which forecasting (point and interval) using Bayesian inference is the main topic. Submitted articles must address the theoretical and computational development of Bayesian forecasting procedures using symmetric or asymmetric probabilities distributions as well as finite mixture of symmetric or asymmetric distributions. However, articles describing the use of well-established computational methods to generate Bayesian forecasting in practical problems using regression models, time series, and survival analysis, among others, as well as articles reviewing Bayesian forecasting considering some specific symmetric or asymmetric distributions, are welcome.
Prof. Dr. Erlandson Ferreira Saraiva
Prof. Dr. Adriano K. Suzuki
Guest Editors
Manuscript Submission Information
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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. Symmetry is an international peer-reviewed open access monthly 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 2400 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 inference
- posterior analysis
- Bayesian forecasting
- Bayesian computational methods
- credible intervals
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