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Statistics & Probability Letters

Statistics & Probability LettersSCIE

国际简称:STAT PROBABIL LETT  参考译名:统计和概率信函

  • 中科院分区

    4区

  • CiteScore分区

    Q3

  • JCR分区

    Q3

基本信息:
ISSN:0167-7152
E-ISSN:1879-2103
是否OA:未开放
是否预警:否
TOP期刊:否
出版信息:
出版地区:NETHERLANDS
出版商:Elsevier
出版语言:English
出版周期:Semimonthly
出版年份:1982
研究方向:数学-统计学与概率论
评价信息:
影响因子:0.9
H-index:56
CiteScore指数:1.6
SJR指数:0.448
SNIP指数:0.894
发文数据:
Gold OA文章占比:16.50%
研究类文章占比:100.00%
年发文量:150
自引率:0
开源占比:0.0596
出版撤稿占比:0
出版国人文章占比:0
OA被引用占比:0.0353...
英文简介 期刊介绍 CiteScore数据 中科院SCI分区 JCR分区 发文数据 常见问题

英文简介Statistics & Probability Letters期刊介绍

Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature.

Statistics & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission.

The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability.

The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published.

期刊简介Statistics & Probability Letters期刊介绍

《Statistics & Probability Letters》自1982出版以来,是一本数学优秀杂志。致力于发表原创科学研究结果,并为数学各个领域的原创研究提供一个展示平台,以促进数学领域的的进步。该刊鼓励先进的、清晰的阐述,从广泛的视角提供当前感兴趣的研究主题的新见解,或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道数学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单,目前已被权威数据库SCIE收录,得到了广泛的认可。

该期刊投稿重要关注点:

Cite Score数据(2024年最新版)Statistics & Probability Letters Cite Score数据

  • CiteScore:1.6
  • SJR:0.448
  • SNIP:0.894
学科类别 分区 排名 百分位
大类:Decision Sciences 小类:Statistics, Probability and Uncertainty Q3 104 / 168

38%

大类:Decision Sciences 小类:Statistics and Probability Q3 173 / 278

37%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础,针对的是前四年发表的论文的引文。CiteScore的意义在于,它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法,而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区Statistics & Probability Letters 中科院分区

中科院 2023年12月升级版 综述期刊:否 Top期刊:否
大类学科 分区 小类学科 分区
数学 4区 STATISTICS & PROBABILITY 统计学与概率论 4区

中科院分区表 是以客观数据为基础,运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据,得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次,类似于“优、良、及格”等。最开始,这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区Statistics & Probability Letters JCR分区

2023-2024 年最新版
按JIF指标学科分区 收录子集 分区 排名 百分位
学科:STATISTICS & PROBABILITY SCIE Q3 102 / 168

39.6%

按JCI指标学科分区 收录子集 分区 排名 百分位
学科:STATISTICS & PROBABILITY SCIE Q3 117 / 168

30.65%

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异,此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此,JCR将期刊按照学科门类和影响因子分为不同的分区,这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

本刊中国学者近年发表论文

  • 1、A deviation inequality for increment of a G-Brownian motion under G-expectation and applications

    Author: Xu, Jie

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 198, Issue , pp. -. DOI: 10.1016/j.spl.2023.109848

  • 2、Adaptive and efficient estimation in the Gaussian sequence model

    Author: Peng, Jingfu

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 195, Issue , pp. -. DOI: 10.1016/j.spl.2022.109762

  • 3、Domain of attraction of quasi-stationary distribution for absorbing Markov processes

    Author: Zhang, Hanjun; Mo, Yongxiang

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 192, Issue , pp. -. DOI: 10.1016/j.spl.2022.109692

  • 4、A lack-of-fit test for quantile regression process models

    Author: Feng, Xingdong; Liu, Qiaochu; Wang, Caixing

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 192, Issue , pp. -. DOI: 10.1016/j.spl.2022.109680

  • 5、Cramer moderate deviations for a supercritical Galton-Watson process

    Author: Doukhan, Paul; Fan, Xiequan; Gao, Zhi-Qiang

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 192, Issue , pp. -. DOI: 10.1016/j.spl.2022.109711

  • 6、Cram?r-type moderate deviations for the log-likelihood ratio of inhomogeneous Ornstein-Uhlenbeck processes

    Author: Cui, Jiazhen; Liu, Qiaojing

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 192, Issue , pp. -. DOI: 10.1016/j.spl.2022.109690

  • 7、Stationary distributions for stochastic differential equations with memory driven by ?-stable processes

    Author: Wang, Wei; Wang, Xiulian

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 195, Issue , pp. -. DOI: 10.1016/j.spl.2022.109766

  • 8、Moderate deviations of hitting times of a family of density-dependent Markov chains

    Author: He, Yuheng; Xue, Xiaofeng

    Journal: STATISTICS & PROBABILITY LETTERS. 2023; Vol. 195, Issue , pp. -. DOI: 10.1016/j.spl.2023.109780

投稿常见问题

通讯方式:ELSEVIER SCIENCE BV, PO BOX 211, AMSTERDAM, NETHERLANDS, 1000 AE。