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STATISTICAL MODELLING

STATISTICAL MODELLING

統(tǒng)計(jì)建模

期刊周期:Quarterly
研究方向:數(shù)學(xué)
影響因子:1.026
通訊地址:SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON, ENGLAND, EC1Y 1SP
官網(wǎng):http://smj.sagepub.com/
投稿地址:https://us.sagepub.com/en-us/nam/statistical-modelling/journal201837#submission-guidelines
審稿速度:>12周,或約稿

  中文簡介

統(tǒng)計(jì)模型:由SAGE出版物代表統(tǒng)計(jì)模型學(xué)會出版的國際期刊。它發(fā)表原創(chuàng)和高質(zhì)量的文章,承認(rèn)統(tǒng)計(jì)建模是應(yīng)用統(tǒng)計(jì)思想的一般框架。提交的報(bào)告必須反映統(tǒng)計(jì)模型的重要發(fā)展、擴(kuò)展和應(yīng)用。該雜志的主要目標(biāo)是發(fā)表原創(chuàng)和高質(zhì)量的文章,承認(rèn)統(tǒng)計(jì)模型作為應(yīng)用統(tǒng)計(jì)思想的一般框架。提交的報(bào)告必須反映統(tǒng)計(jì)模型的重要發(fā)展、擴(kuò)展和應(yīng)用。該雜志還鼓勵提交描述科學(xué)上有趣的、復(fù)雜的或新穎的統(tǒng)計(jì)模型方面的來自廣泛的不同學(xué)科的投稿,以及包含應(yīng)用統(tǒng)計(jì)模型多樣性的投稿。讀者也可以訪問www.statmod.org/journal.htm下載已發(fā)表論文的電子補(bǔ)編,這些補(bǔ)編通常提供代碼和數(shù)據(jù),以便分析的重現(xiàn)性。期刊的一個(gè)重要目標(biāo)和令人興奮的特性是,讀者應(yīng)該能夠重現(xiàn)發(fā)表文章中呈現(xiàn)的結(jié)果,將發(fā)表的技術(shù)應(yīng)用于他們自己的問題,甚至開發(fā)他們自己的方法論擴(kuò)展。為了實(shí)現(xiàn)這一目標(biāo),強(qiáng)烈建議作者通過一個(gè)鏈接到該期刊的網(wǎng)站(http://www.statmod.org/smij/)在互聯(lián)網(wǎng)上提供數(shù)據(jù)和軟件該雜志的目標(biāo)是成為統(tǒng)計(jì)模型的主要資源,包括方法和實(shí)踐。它的目標(biāo)是在性質(zhì)上是多學(xué)科的,促進(jìn)實(shí)質(zhì)性研究領(lǐng)域之間的思想交流,并為不同學(xué)科之間的模型問題的比較、統(tǒng)一和培養(yǎng)提供一個(gè)共同的論壇。該雜志將有三個(gè)主題:新模型的概念和方法的論文新的統(tǒng)計(jì)模型的想法。這些文件將以一個(gè)具有實(shí)際實(shí)質(zhì)性利益的問題為基礎(chǔ),并提供適當(dāng)?shù)臄?shù)據(jù)。僅僅提出和研究基于標(biāo)準(zhǔn)或著名模型的新方法的性質(zhì)的論文不適合在期刊上發(fā)表。關(guān)于有趣的實(shí)際問題的論文的實(shí)際應(yīng)用,這些問題是使用現(xiàn)有的或?qū)ΜF(xiàn)有建模技術(shù)的新改編來解決的。教程和評論與論文最近和前沿的主題在統(tǒng)計(jì)模型。由于“實(shí)際應(yīng)用”手稿在統(tǒng)計(jì)期刊中不如其他兩種常見,因此值得對這類手稿的類型進(jìn)行更具體的說明。原稿應(yīng)描述對某一主題領(lǐng)域的統(tǒng)計(jì)分析,在該主題領(lǐng)域,擬議的分析很少(如果曾經(jīng)有過)在應(yīng)用領(lǐng)域中進(jìn)行。但是,這還不足以接受出版。手稿也應(yīng)該提供一個(gè)全面的文獻(xiàn)回顧的這種類型的數(shù)據(jù)目前如何處理應(yīng)用領(lǐng)域的文獻(xiàn)中,回顧現(xiàn)代統(tǒng)計(jì)方法應(yīng)用于任何應(yīng)用程序的數(shù)據(jù)的類型,并解釋為什么工作是很重要的科目,并提供收益超出當(dāng)前方法應(yīng)用于該領(lǐng)域。所使用的方法應(yīng)該是現(xiàn)代的、相當(dāng)復(fù)雜的(盡管不一定是創(chuàng)新的),并且到目前為止在主題領(lǐng)域的文獻(xiàn)中應(yīng)該很少或沒有應(yīng)用。出版這些手稿的目的是為讀者(包括應(yīng)用領(lǐng)域的讀者)提供一個(gè)機(jī)會,使他們看到該領(lǐng)域數(shù)據(jù)分析發(fā)生革命性變化的潛力。人們還希望,這種出版物將為統(tǒng)計(jì)學(xué)家提供一個(gè)渠道,他們在統(tǒng)計(jì)領(lǐng)域可能因在主題領(lǐng)域中出色、非常規(guī)、聰明和最先進(jìn)的工作而很少得到承認(rèn)。

  英文簡介

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.

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