Special Collection on Statistical Distributions in the Era of Big Data
The Journal of Statistical Distributions and Applications welcomes submissions to a new thematic series exploring the fast-evolving role that statistical distributions play in this so-called era of big data. Particularly, they would welcome methodological research papers that explore how statistical distributions are used to solve problems involving big data.
This thematic series is currently accepting new submissions!
Topics can include, but are not limited to, the following:
- high-dimensional data analysis
- Bayesian methodology
- network inferences
- visualization and generalized modeling
Expository and research papers can make the case for or against the enduring importance of statistical distributions in the era of big data.
The Journal of Statistical Distributions and Applications publishes numerous article types including research papers, methodology papers, reviews, and short reports, all of which can be submitted to this series.
Before submitting your manuscript, please ensure you have carefully read the submission guidelines for the Journal.
The complete manuscript should be submitted through the Journal's submission system. Because this is the same system that processes non-thematic-series submissions, please ensure your paper is distinguishable by answering "yes" to the thematic series question at the Additional Information step, and select the series name from the drop-down menu. In addition, indicate within your cover letter that you wish your manuscript to be considered as part of this series. All submissions will undergo rigorous blinded peer review and accepted articles will be published.
Felix Famoye, Central Michigan University, USA
Carl Lee, Central Michigan University, USA
Submissions will benefit from the following advantages of Open Access publication:
- Rapid publication: Online submission, electronic peer review and production make the process of publishing your article simple and efficient
- High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article
- No space constraints: Publishing online means unlimited space for figures, extensive data and video footage
- Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed.
For editorial queries, please contact this journal's Editors-in-Chief.
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- ISSN: 2195-5832
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