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STATISTICAL SCIENCE

STATISTICAL SCIENCE

STAT SCI
影响因子：3.4
是否综述期刊：否
是否预警：不在预警名单内
是否OA：否
出版国家/地区：UNITED STATES
出版社：Institute of Mathematical Statistics
发刊时间：1986
发刊频率：Quarterly
收录数据库：SCIE/Scopus收录
ISSN：0883-4237

期刊介绍

The central purpose of Statistical Science is to convey the richness, breadth and unity of the field by presenting the full range of contemporary statistical thought at a moderate technical level, accessible to the wide community of practitioners, researchers and students of statistics and probability.
统计科学的中心目的是通过在中等技术水平上呈现当代统计思想的全部范围，向统计和概率的从业者、研究人员和学生的广泛社区传达该领域的丰富性、广度和统一性。
年发文量 35
国人发稿量 3.89
国人发文占比 0.11%
自引率 -
平均录取率0
平均审稿周期 >12周，或约稿
版面费 -
偏重研究方向 数学-统计学与概率论
期刊官网 http://imstat.org/sts/
投稿链接 http://www.e-publications.org/ims/submission/index.php/STS

期刊高被引文献

Bayes, Oracle Bayes and Empirical Bayes
来源期刊：Statistical ScienceDOI：10.1214/18-STS674
Statistical analysis of zero-inflated nonnegative continuous data: A review
来源期刊：Statistical ScienceDOI：10.1214/18-STS681
Comment: Minimalist $g$-Modeling
来源期刊：Statistical ScienceDOI：10.1214/19-STS706
Comment: Spherical Cows in a Vacuum: Data Analysis Competitions for Causal Inference
来源期刊：Statistical ScienceDOI：10.1214/18-STS684
Comment: Strengthening Empirical Evaluation of Causal Inference Methods
来源期刊：Statistical ScienceDOI：10.1214/18-STS690
Comment: Will Competition-Winning Methods for Causal Inference Also Succeed in Practice?
来源期刊：Statistical ScienceDOI：10.1214/18-STS680
Comment: Unreasonable Effectiveness of Monte Carlo
来源期刊：Statistical ScienceDOI：10.1214/18-STS676
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
来源期刊：Statistical ScienceDOI：10.1214/20-sts786
Models as Approximations—Rejoinder
来源期刊：Statistical ScienceDOI：10.1214/19-sts762
Larry Brown’s Work on Admissibility
来源期刊：Statistical ScienceDOI：10.1214/19-sts744
Gaussianization Machines for Non-Gaussian Function Estimation Models
来源期刊：Statistical ScienceDOI：10.1214/19-sts718
Producing Official County-Level Agricultural Estimates in the United States: Needs and Challenges
来源期刊：Statistical ScienceDOI：10.1214/18-STS687
Comment on “Automated Versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition”
来源期刊：Statistical ScienceDOI：10.1214/18-STS689
Comment: Empirical Bayes Interval Estimation
来源期刊：Statistical ScienceDOI：10.1214/19-STS708
Comment: Variational Autoencoders as Empirical Bayes
来源期刊：Statistical ScienceDOI：10.1214/19-STS710
Comment: Statistical Inference from a Predictive Perspective
来源期刊：Statistical ScienceDOI：10.1214/19-sts748
Gaussian integrals and Rice series in crossing distributions : to compute the distribution of maxima and other features of Gaussian processes
来源期刊：Statistical ScienceDOI：10.1214/18-STS662
A Conversation with Piet Groeneboom
来源期刊：Statistical ScienceDOI：10.1214/18-STS663
A Conversation with Robert E. Kass
来源期刊：Statistical ScienceDOI：10.1214/18-STS691
A Conversation with Noel Cressie
来源期刊：Statistical ScienceDOI：10.1214/19-STS695
Larry Brown’s Contributions to Parametric Inference, Decision Theory and Foundations: A Survey
来源期刊：Statistical ScienceDOI：10.1214/19-sts717
Comment: Models Are Approximations!
来源期刊：Statistical ScienceDOI：10.1214/19-sts746
A Conversation with Peter Diggle
来源期刊：Statistical ScienceDOI：10.1214/19-sts703
Statistical Theory Powering Data Science
来源期刊：Statistical ScienceDOI：10.1214/19-sts754
A Kernel Regression Procedure in the 3D Shape Space with an Application to Online Sales of Children’s Wear
来源期刊：Statistical ScienceDOI：10.1214/18-STS675
Rejoinder: Response to Discussions and a Look Ahead
来源期刊：Statistical ScienceDOI：10.1214/18-STS688
Comment: Causal Inference Competitions: Where Should We Aim?
来源期刊：Statistical ScienceDOI：10.1214/18-STS679
Discussion of Models as Approximations I & II
来源期刊：Statistical ScienceDOI：10.1214/19-sts722
A Conversation with Dick Dudley
来源期刊：Statistical ScienceDOI：10.1214/18-STS678
Comment on Models as Approximations, Parts I and II, by Buja et al.
来源期刊：Statistical ScienceDOI：10.1214/19-sts723
Comment: Contributions of Model Features to BART Causal Inference Performance Using ACIC 2016 Competition Data
来源期刊：Statistical ScienceDOI：10.1214/18-STS682

质量指标占比

研究类文章占比 OA被引用占比 撤稿占比 出版后修正文章占比
91.43%10.11%--

相关指数

影响因子
影响因子
年发文量
自引率
Cite Score

预警情况

查看说明
时间 预警情况
2025年03月发布的2025版不在预警名单中
2024年02月发布的2024版不在预警名单中
2023年01月发布的2023版不在预警名单中
2021年12月发布的2021版不在预警名单中
2020年12月发布的2020版不在预警名单中
*来源：中科院《 国际期刊预警名单》

JCR分区

WOS分区等级：Q1区
版本 按学科 分区
WOS期刊SCI分区
WOS期刊SCI分区
WOS期刊SCI分区是指SCI官方（Web of Science）为每个学科内的期刊按照IF数值排 序，将期刊按照四等分的方法划分的Q1-Q4等级，Q1代表质量最高，即常说的1区期刊。
（2024-2025年最新版）
STATISTICS & PROBABILITY
Q1

中科院分区

查看说明
版本 大类学科 小类学科 Top期刊 综述期刊
2025年3月最新升级版
数学1区
STATISTICS & PROBABILITY 统计学与概率论
1区
是
否
2023年12月升级版
数学1区
STATISTICS & PROBABILITY 统计学与概率论
1区
否
否
2022年12月旧的升级版
数学2区
STATISTICS & PROBABILITY 统计学与概率论
2区
否
否