Statistical Inference for Stochastic Processes is an international journal publishing articles on parametric and nonparametric inference for discrete- and continuous-time stochastic processes, and their applications to biology, chemistry, physics, finance, economics, and other sciences.

Peer review is conducted using Editorial Manager®, supported by a database of international experts. This database is shared with the journal, Extremes.

Journal information

Co-Editor-in-Chief
  • Siegfried Hörmann,
  • Arnaud Gloter
Publishing model
Hybrid (Transformative Journal). How to publish with us, including Open Access

Journal metrics

86 days
Submission to first decision (Median)
14,785 (2021)
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Latest articles

  1. Preface

    Authors

    • O Lepski
    • Content type: Editorial
    • Published: 28 April 2022
    • Pages: 1 - 1
This journal has 22 open access articles

About this journal

Electronic ISSN
1572-9311
Print ISSN
1387-0874
Abstracted and indexed in
  1. ANVUR
  2. Australian Business Deans Council (ABDC) Journal Quality List
  3. BFI List
  4. Baidu
  5. CLOCKSS
  6. CNKI
  7. CNPIEC
  8. Current Index to Statistics
  9. Dimensions
  10. EBSCO Discovery Service
  11. EconLit
  12. Emerging Sources Citation Index
  13. Google Scholar
  14. Japanese Science and Technology Agency (JST)
  15. Mathematical Reviews
  16. Naver
  17. Norwegian Register for Scientific Journals and Series
  18. OCLC WorldCat Discovery Service
  19. Portico
  20. ProQuest-ExLibris Primo
  21. ProQuest-ExLibris Summon
  22. Research Papers in Economics (RePEc)
  23. SCImago
  24. SCOPUS
  25. TD Net Discovery Service
  26. UGC-CARE List (India)
  27. Wanfang
  28. zbMATH
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