中文簡介

《應(yīng)用統(tǒng)計學(xué)雜志》是一份世界領(lǐng)先的期刊，它為統(tǒng)計學(xué)家和實務(wù)工作者提供了一個交流的平臺，讓他們能夠明智地應(yīng)用統(tǒng)計原則，并創(chuàng)新統(tǒng)計方法。生物及生物醫(yī)學(xué)商業(yè)、經(jīng)濟、管理和金融計算機科學(xué)與信息技術(shù)數(shù)據(jù)科學(xué)生態(tài)教育工程遺傳學(xué)和基因組學(xué)醫(yī)學(xué)及相關(guān)學(xué)科運籌學(xué)社會科學(xué)編輯政策是發(fā)表嚴謹、清晰、易懂的論文，研究針對現(xiàn)實生活中的統(tǒng)計問題而開發(fā)的方法，預(yù)計這些方法將產(chǎn)生廣泛的科學(xué)影響。避免純粹的理論論文，但可以考慮那些明顯顯示具體應(yīng)用潛力的理論發(fā)展論文。強烈鼓勵基于某一主題領(lǐng)域的真正挑戰(zhàn)，展示統(tǒng)計技術(shù)的創(chuàng)造性發(fā)展的論文。該雜志發(fā)表原創(chuàng)研究論文、評論文章和簡短的申請說明。一般來說，原始的研究論文應(yīng)該在一個領(lǐng)域提出一到兩個挑戰(zhàn)，包括相關(guān)的數(shù)據(jù)，提供一個新的方法來解決挑戰(zhàn)，并證明所提出的方法已經(jīng)回答了之前相關(guān)現(xiàn)有方法沒有正確或最佳地解決的問題。綜述文章應(yīng)側(cè)重于一種或多種目前已被其他學(xué)科廣泛使用的統(tǒng)計研究方法，以及應(yīng)用和對未來方向的討論。應(yīng)用說明應(yīng)至少說明對任何學(xué)科的數(shù)據(jù)挑戰(zhàn)創(chuàng)新地應(yīng)用現(xiàn)有統(tǒng)計方法，并有令人信服的結(jié)果。

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英文簡介

Journal of Applied Statistics is a world-leading journal which provides a forum for communication among statisticians and practitioners for judicious application of statistical principles and innovations of statistical methodology motivated by current and important real-world examples across a wide range of disciplines, including, but not limited to:biological and biomedical sciencesbusiness, economics, management and financecomputer science and information technologydata scienceecologyeducationengineeringgenetics and genomics medicine and related disciplinesoperations researchsocial sciencesThe editorial policy is to publish rigorous, clear and accessible papers on methods developed for real-life statistical problems, and which are anticipated to have a broad scientific impact. Purely theoretical papers are avoided but those on theoretical developments which clearly exhibit concrete applied potential may be considered. Papers demonstrating creative development of statistical techniques based on a true challenge in a subject area are strongly encouraged. The Journal publishes original research papers, review articles, and short application notes.In general, original research papers should present one or two challenges in an area, include relevant data, provide a novel method to solve challenges, and demonstrate that the proposed method has answered questions that were not properly or optimally addressed before by relevant existing methods. Review articles should focus on one or more current statistical research methods that have been widely used by other discipline(s), along with applications and a discussion for future directions. Application notes should at least illustrate innovative application of existing statistical method(s) to a data challenge in any discipline with convincing findings.