Computational Statistics (CompStat) is an international journal that fosters the publication of applications and methodological research in the field of computational statistics. The journal provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge-based systems, and Bayesian computing.
CompStat papers emphasize the contribution to and influence of computing on statistics and vice versa. The journal also publishes hardware, software, and package reports.
Officially cited as: Comput Stat
- Fosters the publication of applications and methodological research in the field of computational statistics
- Emphasizes the contribution to and influence of computing on statistics and vice versa
- Provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics
- Publishes hardware, software, and package reports
Journal information
- Editor-in-Chief
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- Wataru Sakamoto
- Editors
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- Usha Govindarajulu,
- Philippe Vieu
- Publishing model
- Hybrid. Open Access options available
Journal metrics
- 0.744 (2019)
- Impact factor
- 0.960 (2019)
- Five year impact factor
- 85 days
- Submission to first decision
- 448 days
- Submission to acceptance
- 101,110 (2019)
- Downloads
Latest issue
Latest articles
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Estimation of parameters in multivariate wrapped models for data on a p-torus
Authors (first, second and last of 4)
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R package for statistical inference in dynamical systems using kernel based gradient matching: KGode
Authors (first, second and last of 5)
Journal updates
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COVID-19 and impact on peer review
As a result of the significant disruption that is being caused by the COVID-19 pandemic we are very aware that many researchers will have difficulty in meeting the timelines associated with our peer review process during normal times. Please do let us know if you need additional time. Our systems will continue to remind you of the original timelines but we intend to be highly flexible at this time.
About this journal
- Electronic ISSN
- 1613-9658
- Print ISSN
- 0943-4062
- Abstracted and indexed in
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- ABS Academic Journal Quality Guide
- ACM Digital Library
- CNKI
- Current Index to Statistics
- DBLP
- Dimensions
- EBSCO Academic Search
- EBSCO Discovery Service
- Google Scholar
- Institute of Scientific and Technical Information of China
- Japanese Science and Technology Agency (JST)
- Journal Citation Reports/Science Edition
- Mathematical Reviews
- Naver
- OCLC WorldCat Discovery Service
- ProQuest ABI/INFORM
- ProQuest Advanced Technologies & Aerospace Database
- ProQuest Business Premium Collection
- ProQuest Central
- ProQuest Civil Engineering Abstracts
- ProQuest Computer Science
- ProQuest Computer and Information Systems Abstracts
- ProQuest Engineering
- ProQuest Health Research Premium Collection
- ProQuest Materials Science and Engineering Database
- ProQuest Mechanical and Transportation Engineering Abstracts
- ProQuest Public Health Database
- ProQuest Research Library
- ProQuest SciTech Premium Collection
- ProQuest Science Database
- ProQuest Technology Collection
- ProQuest-ExLibris Primo
- ProQuest-ExLibris Summon
- Psyndex
- Research Papers in Economics (RePEc)
- SCImago
- SCOPUS
- Science Citation Index Expanded (SciSearch)
- UGC-CARE List (India)
- zbMATH
- Copyright information
