Statistics and Its Interface

ISSN Print 1938-7989  ISSN Online 1938-7997

4 issues per year

Editors-in-Chief

Ming-Hui Chen (University of Connecticut)

Yuedong Wang (University of California at Santa Barbara)

HomeEditorsSubmissionsAcceptedRead Online

Aims and Scope

Explores the interface between the field of statistics and other disciplines, including but not limited to: biomedical sciences, geosciences, computer sciences, engineering, and social and behavioral sciences. Publishes high-quality articles in broad areas of statistical science, emphasizing substantive problems, sound statistical models and methods, clear and efficient computational algorithms, and insightful discussions of the motivating problems.

Publication

Publishing since 2008.

4 issues per year.

Citation Report Metrics

Journal Citation Reports: Clarivate Analytics

Coverage Year: 2020

Total Citations: 757

Journal Impact Factor: 0.582

5-Year Impact Factor: 0.827

Immediacy Index: 0.167

Eigenfactor: 0.00119

Sponsorship

Statistics and Its Interface is partially sponsored by the Yau Mathematical Sciences Center (MSC) of Tsinghua University.

Special Notices

Call for Papers: Special Issue celebrating Professor Lincheng Zhao’s 80th Birthday

Lincheng Zhao is an internationally recognized scholar and is prominent for his contributions in M-estimation, Nonparametric Statistics, Signal Processing and Limit Theorems in Probability Theory and Statistics. Ever since 1982, he has been teaching at the University of Science and Technology of China, which has nurtured many world-class scholars in Statistics. In 2022, he will celebrate his 80th birthday. To pay a tribute to his illustrious career and long-term service, Statistics and Its Interface (SII) is pleased to announce a special issue of invited contributions to honor his birthday.

Contributions are invited on any topic within the scope of the journal.

The submission deadline for this special issue is December 31, 2022. Please submit your paper online through SII’s electronic journal management system. (If you have not yet registered with the system, you must first do so, here).

In the Comments box, please indicate that your submission is “for the special issue in honor of Professor Zhao.”

Before submitting your manuscript, please make sure that it has not been previously published or submitted elsewhere for consideration.

A single-blind peer-review method will be used on all submissions.

General information about submitting a paper to SII can be found by clicking the “Submissions” tab above.

  • Steven Shuangge Ma (Co-Guest Editor), Yale University
  • Tiejun Tong (Co-Guest Editor), Hong Kong Baptist University
  • Jinfeng Xu (Co-Guest Editor), Hong Kong University
  • Hong Zhang (Co-Guest Editor), University of Science and Technology of China
  • Ming-Hui Chen (Co-Editor-in-Chief), University of Connecticut
  • Yuedong Wang (Co-Editor-in-Chief), University of California, Santa Barbara

Call for Papers: Special Issue on Modern Data Science and Applications

The editors of Statistics and Its Interface (SII) are now accepting submissions for a special issue on Modern Data Science and Applications. Because of the rapid growth and diversification of research in current data science, the area is becoming more popular and widely employed across a wide range of disciplines such as medicine and public health as well as in the engineering, finance and business fields. Statistics and computational approaches are applied to real-world phenomena and problems in data science, which explores new types of data, concepts, experiments, descriptions, estimates, and forecasts. Moreover, new questions are being posed based on novel data and findings from Data Science approaches, as well as on previously unexplored topics. Thus, we encourage submissions based on original, thorough research in all scientific fields.

The submission deadline for this special issue is December 1, 2022. Please submit your paper online through SII’s electronic journal management system. (If you have not yet registered with the system, you must first do so, here).

In the Comments box, please indicate that your submission is “for the Special Issue on modern data science and applications.”

Before submitting your manuscript, please make sure that it has not been previously published or submitted elsewhere for consideration.

A single-blind peer-review method will be used on all submissions.

General information about submitting a paper to SII can be found by clicking the “Submissions” tab above.

  • Linglong Kong (Co-Guest Editor), University of Alberta
  • Xinyuan Song (Co-Guest Editor), The Chinese University of Hong Kong
  • Niansheng Tang (Co-Guest Editor), Yunnan University
  • Xueqin Wang (Co-Guest Editor), University of Science and Technology of China
  • Hongtu Zhu (Co-Guest Editor), The University of North Carolina at Chapel Hill
  • Ming-Hui Chen (Co-Editor-in-Chief), University of Connecticut
  • Yuedong Wang (Co-Editor-in-Chief), University of California, Santa Barbara

Call for Papers: Special Issue on Statistical Learning of Tensor Data

Statistics and Its Interface (SII) invites submissions for a special issue on statistical learning of tensor data. Tensor, or multidimensional array, is arising in a wide range of scientific and business applications. Research on learning of tensor data has been rapidly expanding during the last few decades, extending to modern datasets such as medical images, social network, and personalized recommendation systems, and widely used in many fields including medicine, biology, public health, engineering, finance, economics, sports analytics, and environmental sciences. The rapid developments also lead to many challenges in estimation, inference, prediction, and computation in learning of tensor data. SII promotes interface between statistical theory, methodology and applications. Thus, we strongly encourage innovative theory, methodology and novel applications in statistical learning of tensor data. The review papers related with statistical learning of tensor data are also welcomed. Your papers, once accepted, will be published together in a special issue of SII.

The submission deadline for this special issue is October 1, 2022. Please submit your paper online through SII’s electronic journal management system. (If you have not yet registered with the system, you must first do so, here).

In the Comments box, please indicate that your submission is “for the Special Issue on statistical learning of tensor data.”

All submissions will go through a regular review process. As the editors for this special issue, we will handle the peer review carefully and in a timely manner.

With your support and collaboration, we are confident that this special issue will be a success and will reflect state-of-art of research at the frontier of this vital and rapidly developing area. We look forward to receiving your papers in due course.

  • Guanyu Hu (Co-Guest Editor), University of Missouri
  • HaiYing Wang (Co-Guest Editor), University of Connecticut
  • Jing Wu (Co-Guest Editor), University of Rhode Island
  • Anru Zhang (Co-Guest Editor), Duke University
  • Ming-Hui Chen (Co-Editor-in-Chief), University of Connecticut
  • Yuedong Wang (Co-Editor-in-Chief), University of California, Santa Barbara