SCI SCIE
STATISTICAL MODELLING 期刊简介
英文简介:

Statistical Modelling: An International Journal is published by SAGE Publications on behalf of the Statistical Modelling Society. It publishes original and high-quality articles that recognize statistical modelling as the general framework for the application of statistical ideas. Submissions must reflect important developments, extensions, and applications in statistical modelling. The primary aim of the journal is to publish original and high-quality articles that recognize statistical modelling as the general framework for the application of statistical ideas. Submissions must reflect important developments, extensions, and applications in statistical modelling. The journal also encourages submissions that describe scientifically interesting, complex or novel statistical modelling aspects from a wide diversity of disciplines, and submissions that embrace the diversity of applied statistical modelling. Readers are also encouraged to visit www.statmod.org/journal.htm to download electronic supplements of published papers, which among other items, often provide code and data for reproducibility of analyses. An important objective and exciting feature of the journal is that the reader should be able to reproduce the results presented in published articles, apply the published techniques to their own problems, and even develop their own extensions of the methodology. To achieve this authors are strongly encouraged to make data and software available over the internet through a website linked to the journal: http://www.statmod.org/smij/ The journal aims to be the major resource for statistical modelling, covering both methodology and practice. Its goal is to be multidisciplinary in nature, promoting the cross-fertilization of ideas between substantive research areas, as well as providing a common forum for the comparison, unification and nurturing of modelling issues across different subjects. The journal will have three main themes: New Modelling Concepts and Approaches for papers on new statistical modelling ideas. These papers will be based upon a problem of real substantive interest with appropriate data. Papers that merely propose and study the properties of new methodology based on a standard or well-known model are not appropriate for publication in the journal. Practical Applications for papers on interesting practical problems which are addressed using an existing or a novel adaptation of an existing modelling technique. Tutorials & Reviews with papers on recent and cutting edge topics in statistical modelling. Since "Practical Applications" manuscripts are less common in statistics journals than the other two types, it is worth being more specific concerning the types of manuscripts that fall into this category. Manuscripts should describe statistical analyses of a subject area, where the proposed analyses have rarely (if ever) been done in the application field. This is not, however, sufficient for acceptance for publication. Manuscripts should also provide a thorough literature review of how data of this type are currently handled in the literature of the application area, a review of any applications of modern statistical methodology applied to data of its type in the area, and justification as to why the work is important to the subject area, and provides gains beyond current methodology applied to the field. The methodology used should be modern and reasonably sophisticated (although not necessarily innovative) and should have few or no applications so far in the subject area literature. The intention in publishing such manuscripts is to provide an opportunity for readers (including those from the application area) to see the potential to revolutionize data analysis in the field. It is also hoped that such publication would provide an outlet for statisticians who may get little recognition in the statistics field for excellent, non-routine, clever, state-of-the-art work in subject areas.

中文简介:(来自Google、百度翻译)

统计模型:由SAGE出版物代表统计模型学会出版的国际期刊。它发表原创和高质量的文章,承认统计建模是应用统计思想的一般框架。提交的报告必须反映统计模型的重要发展、扩展和应用。 该杂志的主要目标是发表原创和高质量的文章,承认统计模型作为应用统计思想的一般框架。提交的报告必须反映统计模型的重要发展、扩展和应用。该杂志还鼓励提交描述科学上有趣的、复杂的或新颖的统计模型方面的来自广泛的不同学科的投稿,以及包含应用统计模型多样性的投稿。读者也可以访问www.statmod.org/journal.htm下载已发表论文的电子补编,这些补编通常提供代码和数据,以便分析的重现性。 期刊的一个重要目标和令人兴奋的特性是,读者应该能够重现发表文章中呈现的结果,将发表的技术应用于他们自己的问题,甚至开发他们自己的方法论扩展。为了实现这一目标,强烈建议作者通过一个链接到该期刊的网站(http://www.statmod.org/smij/)在互联网上提供数据和软件 该杂志的目标是成为统计模型的主要资源,包括方法和实践。它的目标是在性质上是多学科的,促进实质性研究领域之间的思想交流,并为不同学科之间的模型问题的比较、统一和培养提供一个共同的论坛。 该杂志将有三个主题: 新模型的概念和方法的论文新的统计模型的想法。这些文件将以一个具有实际实质性利益的问题为基础,并提供适当的数据。仅仅提出和研究基于标准或著名模型的新方法的性质的论文不适合在期刊上发表。 关于有趣的实际问题的论文的实际应用,这些问题是使用现有的或对现有建模技术的新改编来解决的。 教程和评论与论文最近和前沿的主题在统计模型。 由于“实际应用”手稿在统计期刊中不如其他两种常见,因此值得对这类手稿的类型进行更具体的说明。原稿应描述对某一主题领域的统计分析,在该主题领域,拟议的分析很少(如果曾经有过)在应用领域中进行。但是,这还不足以接受出版。手稿也应该提供一个全面的文献回顾的这种类型的数据目前如何处理应用领域的文献中,回顾现代统计方法应用于任何应用程序的数据的类型,并解释为什么工作是很重要的科目,并提供收益超出当前方法应用于该领域。所使用的方法应该是现代的、相当复杂的(尽管不一定是创新的),并且到目前为止在主题领域的文献中应该很少或没有应用。 出版这些手稿的目的是为读者(包括应用领域的读者)提供一个机会,使他们看到该领域数据分析发生革命性变化的潜力。人们还希望,这种出版物将为统计学家提供一个渠道,他们在统计领域可能因在主题领域中出色、非常规、聪明和最先进的工作而很少得到承认。

期刊ISSN
1471-082X
最新的影响因子
2.039
最新CiteScore值
1.18
最新自引率
17.10%
期刊官方网址
http://smj.sagepub.com/
期刊投稿网址
https://us.sagepub.com/en-us/nam/statistical-modelling/journal201837#submission-guidelines
通讯地址
SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON, ENGLAND, EC1Y 1SP
偏重的研究方向(学科)
数学-统计学与概率论
出版周期
Quarterly
平均审稿速度
>12周,或约稿
出版年份
2001
出版国家/地区
ENGLAND
是否OA
No
SCI期刊coverage
Science Citation Index Expanded(科学引文索引扩展)
NCBI查询
PubMed Central (PMC)链接 全文检索(pubmed central)
STATISTICAL MODELLING 期刊中科院JCR 评价数据
最新中科院JCR分区
大类(学科)
小类(学科)
JCR学科排名
数学
STATISTICS & PROBABILITY(统计学和概率) 2区
40/123
最新的影响因子
2.039
最新公布的期刊年发文量
年度总发文量 年度论文发表量 年度综述发表量
18 18 0
总被引频次 668
特征因子 0.001750
影响因子趋势图
2007年以来影响因子趋势图(整体平稳趋势)
STATISTICAL MODELLING 期刊CiteScore评价数据
最新CiteScore值
1.18
=
引文计数(2018) 文献(2015-2017)
=
103次引用 87篇文献
文献总数(2014-2016) 87
被引用比率
44%
SJR
1.269
SNIP
0.846
CiteScore排名
序号 类别(学科) 排名 百分位
1 Mathematics Statistics and Probability #
CiteScore趋势图
CiteScore趋势图
scopus涵盖范围
scopus趋势图
STATISTICAL MODELLING 投稿经验(由下方点评分析获得,0人参与,95人阅读)
偏重的研究方向:
  • 暂无
投稿录用比例: 暂无
审稿速度: 暂无
分享者 点评内容
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基础信息
中科院JCR评价数据
CiteScore评测数据
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