STAT SURV
| WoS 期刊 JCR 分区 (2026 · JIF) | 综合 ESCI | Q1 | ||
|---|---|---|---|---|
| 学科 | 收录集 | JIF 分区 | JIF 排名 | JIF 百分位 |
| 统计学与概率论 Statistics & Probability | ESCI | Q1 | 3/170 |
98.2%
|
| 学科 | 收录集 | JCI 分区 | JCI 排名 | JCI 百分位 |
|---|---|---|---|---|
| 统计学与概率论 Statistics & Probability | ESCI | Q1 | 1/156 JCI 6.25 |
100.0%
|
Statistics Surveys is a premier, open-access journal dedicated to the publication of high-quality review and survey articles in the field of statistics and probability. Published by the Institute of Mathematical Statistics (IMS), the journal serves as a vital resource for the statistical community, offering comprehensive and accessible overviews of both established and emerging areas of research. Its scope encompasses a wide range of topics, including theoretical developments, methodological innovations, computational statistics, and applications across the sciences. Each contribution is designed to synthesize a substantial body of literature, providing readers with an authoritative entry point into a specific subfield, highlighting key results, open problems, and future directions. The journal exclusively publishes review and survey articles, distinguishing it from outlets that focus primarily on original research findings. This format ensures that each paper offers significant pedagogical and reference value, making it an indispensable tool for graduate students, academic researchers, and practicing statisticians seeking to broaden their expertise or stay abreast of developments beyond their immediate specialization. A notable feature of Statistics Surveys is its open-access model, ensuring that all content is freely and permanently available online to a global audience, thereby maximizing the dissemination and impact of its scholarly contributions. With a 2026 Impact Factor of 8.2000 and placement in the JCR Q1 quartile, the journal is recognized as a leading publication within its category, reflecting the high quality, rigor, and influence of the surveys it publishes. This standing underscores its role as a cornerstone resource for the statistical sciences.