Statistical Forecasting: Theories, Methods and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 1390
Special Issue Editor
Interests: model selection; post-estimation and prediction; shrinkage and empirical Bayes; Bayesian data analysis; machine learning; business; information science; statistical genetics; image analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Statistical forecasting is widely applicable in various fields, such as economics, finance, meteorology, environmental sciences, biology, and healthcare, and it plays a crucial role in decision making and planning by individuals, organizations, and industries. It helps in identifying patterns, trends, and relationships in historical data to make informed predictions about future events or outcomes.
This Special Issue "Statistical Forecasting: Theories, Methods and Applications" in Mathematics aims to explore this important field and the use of statistical techniques to predict future values or trends. The focus is on the role and effect of various statistical methods in data prediction.
We welcome researchers to explore the latest advancements and challenges in statistical forecasting and to promote the exchange of ideas and knowledge in this field via research on the theoretical aspects of statistical forecasting. The topics of interest include, but are not limited to, time series analysis, regression analysis, machine learning techniques, Bayesian data analysis, multivariate analysis, and statistical diagnostics. Additionally, we place equal emphasis on applied aspects of statistical forecasting, and the role and effect of various statistical methods in data prediction; the fields of application include, but are not limited to, economics, finance, and environment and health sciences.
Prof. Dr. S. Ejaz Ahmed
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
- statistical forecasting
- predictive modeling
- Bayesian statistics
- distribution theory and its applications
- risk forecasting
- financial statistics
