About this journal

Aims and scope

The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches.

Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed. Publication office: Taylor & Francis, Inc., 530 Walnut Street, Suite 850, Philadelphia, PA 19106.

The journal emphasizes both readability and relevance to all statisticians and does not exclusively cater to a handful of specialists in the field of sequential analysis. Readership includes statisticians, mathematicians, biostatisticians, scientists, probabilists, clinicians, quality control managers, and engineers.

Journal metrics

Usage

  • 14K annual downloads/views

Citation metrics

  • 0.6 (2023) Impact Factor
  • 0.7 (2023) 5 year IF
  • 1.4 (2023) CiteScore (Scopus)
  • 0.841 (2023) SNIP
  • 0.414 (2023) SJR

Speed/acceptance

  • 2 days avg. from submission to first decision
  • 72 days avg. from submission to first post-review decision
  • 62 days avg. from acceptance to online publication
  • 30% acceptance rate

Editorial board

Editor-in-Chief

Nitis Mukhopadhyay
Department of Statistics
CLAS Bldg, Box 4120
University of Connecticut
Storrs, CT 06269-4120, USA
Tel: 860-486-6144
Fax: 860-486-4113
E-mail: [email protected]


Associate Editors

Makoto Aoshima - Institute of Mathematics, University of Tsukuba, Ibaraki, JAPAN
Michael Baron -
Department of Mathematics and Statistics, American University, Washington, D.C., U.S.A.
Debanjan Bhattacharjee -
Department of Mathematics, Utah Valley University, Orem, UT, U.S.A
Marco Bonetti - Bocconi University, Milan, ITALY
Elena Buzaianu -
Department of Mathematics and Statistics, University of North Florida, Jacksonville, U.S.A.
Hock Peng Chan -
Department of Statistics & Applied Probability, National University of Singapore, Singapore, REPUBLIC OF SINGAPORE
Yuan-chin Ivan Chang - Institute of Statistical Science Academia Sinica, Taipei, TAIWAN
Bhargab Chattopadhyay - Indian Istitute of Information Technology Vadodara, Gujarat, INDIA
Saibal Chattopadhyay - Operations Management Group, Indian Institute of Management Calcutta, Kolkata, INDIA
Pinyuen Chen - Department of Mathematics, Syracuse University, Syracuse, NY, U.S.A.
Pankaj Choudhary
- Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX, U.S.A.
D. Stephen Coad -
School of Mathematical Sciences, University of London, UNITED KINGDOM
Shyamal Krishna De - School of Mathematical Sciences, National Institute of Science Education and Research, INDIA
Joe Glaz -
Department of Statistics, University of Connecticut, Storrs, CT, U.S.A.
David Goldsman -
School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, U.S.A.
Edit Gombay -
Department of Mathematical & Statistical Sciences, University of Alberta, Edmonton, Alberta, CANADA
Marie Huskova -
Department of Statistics, Charles University, Prague, CZECH REPUBLIC
Kartlos Kachiashvili - Georgian Technical University and I. Vekua Institute of Applied Mathematics, Tbilisi State University, GEORGIA
Jan Kalina -
Institute of Computer Science of the Czech Academy of Sciences, CZECH REPUBLIC
Sangyeol Lee -
Department of Statistics, Seoul National University, Seoul, KOREA
Yajun Mei - H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A.
Amitava Mukherjee - XLRI- Xavier School of Management, Jamshedpur, INDIA
Ivair Ramos Silva - Department of Statistics, Federal University of Ouro Preto MG, BRAZIL
William F. Rosenberger - School of Information Technology and Engineering, George Mason University, Fairfax, VA, U.S.A.
Wolfgang Schmid - Department of Statistics, European University, Frankfurt (Oder), GERMANY
T. K. S. Solanky -
Department of Mathematics, University of New Orleans, New Orleans, LA, U.S.A.
T. N. Sriram -
Department of Statistics, University of Georgia, Athens, GA, U.S.A.
Ansgar Steland -
Institute of Statistics, RWTH Aachen University, Aachen, GERMANY
Alexander Tartakovsky - Department of Statistics, University of Connecticut, Storrs, CT, U.S.A.
H.K. Tony Ng -
Department of Statistical Science, Southern Methodist University, Dallas, TX, U.S.A.
Yaser Samadi - Department of Mathematics, Southern Illinois University, Carbondale, IL, U.S.A
Tae Yang - Department of Mathematics, Myongji University, Yongin, KOREA
Kazuyoshi Yata - Institute of Mathematics, University of Tsukuba, Ibaraki, JAPAN
Yao Xie-
H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A .
Shelley Zacks -
Department of Mathematical Sciences, Binghamton University, Binghamton, NY, U.S.A.
Gideon K.D. Zamba - Department of Biostatistics, University of Iowa, Iowa City, IA, U.S.A.

Abstracting and indexing

Sequential Analysis is Abstracted and Indexed in the following:

CSA Technology Research Database
Current Index to Statistics
Genamics JournalSeek
MathSciNet
Mathematical Reviews
Scopus
Statistical Theory and Method Abstracts
zbMATH

Open access

Sequential Analysis is a hybrid open access journal that is part of our Open Select publishing program, giving you the option to publish open access. Publishing open access means that your article will be free to access online immediately on publication, increasing the visibility, readership, and impact of your research.

Why choose open access?

  1. Increase the discoverability and readership of your article
  2. Make an impact and reach new readers, not just those with easy access to a research library
  3. Freely share your work with anyone, anywhere
  4. Comply with funding mandates and meet the requirements of your institution, employer or funder
  5. Rigorous peer review for every open access article

Article Publishing Charges (APC)

If you choose to publish open access in this journal you may be asked to pay an Article Publishing Charge (APC). You may be able to publish your article at no cost to yourself or with a reduced APC if your institution or research funder has an open access agreement or membership with Taylor & Francis.

Use our APC finder to calculate your article publishing charge

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