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
  • Wataru Sakamoto
Editors
  • Usha Govindarajulu,
  • Philippe Vieu
Publishing model
Hybrid. Open Access options available

Journal metrics

0.68 (2018)
Impact factor
1.074 (2018)
Five year impact factor
85 days
Submission to first decision
445 days
Submission to acceptance
101,110 (2019)
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Latest issue

Volume 35

Issue 2, June 2020

Special Issue: Service Data Analytics and Business Intelligence(Pages 423-557)

Latest articles

This journal has 55 open access articles

Journal updates

  • 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.

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About this journal

Electronic ISSN
1613-9658
Print ISSN
0943-4062
Abstracted and indexed in
  1. ABS Academic Journal Quality Guide
  2. ACM Digital Library
  3. CNKI
  4. Current Index to Statistics
  5. EBSCO Academic Search
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  7. Gale
  8. Gale Academic OneFile
  9. Gale InfoTrac
  10. Google Scholar
  11. Institute of Scientific and Technical Information of China
  12. Japanese Science and Technology Agency (JST)
  13. Journal Citation Reports/Science Edition
  14. Mathematical Reviews
  15. Naver
  16. OCLC WorldCat Discovery Service
  17. ProQuest ABI/INFORM
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  35. Psyndex
  36. Research Papers in Economics (RePEc)
  37. SCImago
  38. SCOPUS
  39. Science Citation Index Expanded (SciSearch)
  40. zbMATH
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