Skip to main content
Log in

Statistical Inference for Stochastic Processes

An International Journal devoted to Time Series Analysis and the Statistics of Continuous Time Processes and Dynamical Systems

Publishing model:

Overview

Statistical Inference for Stochastic Processes is an international journal publishing articles on parametric and nonparametric inference for discrete- and continuous-time stochastic processes.

  • The journal's focus extends to applications in diverse sciences like biology, chemistry, physics, finance, and economics.

Co-Editor-in-Chief
  • Siegfried Hörmann,
  • Arnaud Gloter
Impact factor
0.8 (2022)
5 year impact factor
0.8 (2022)
Submission to first decision (median)
11 days
Downloads
39,108 (2023)

Latest articles

Journal information

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
  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
  21. Research Papers in Economics (RePEc)
  22. SCImago
  23. SCOPUS
  24. TD Net Discovery Service
  25. UGC-CARE List (India)
  26. Wanfang
  27. zbMATH
Copyright information

Rights and permissions

Springer policies

© Springer Nature B.V.

Navigation