中文简介

《应用统计学杂志》是一份世界领先的期刊，它为统计学家和实务工作者提供了一个交流的平台，让他们能够明智地应用统计原则，并创新统计方法。生物及生物医学商业、经济、管理和金融计算机科学与信息技术数据科学生态教育工程遗传学和基因组学医学及相关学科运筹学社会科学编辑政策是发表严谨、清晰、易懂的论文，研究针对现实生活中的统计问题而开发的方法，预计这些方法将产生广泛的科学影响。避免纯粹的理论论文，但可以考虑那些明显显示具体应用潜力的理论发展论文。强烈鼓励基于某一主题领域的真正挑战，展示统计技术的创造性发展的论文。该杂志发表原创研究论文、评论文章和简短的申请说明。一般来说，原始的研究论文应该在一个领域提出一到两个挑战，包括相关的数据，提供一个新的方法来解决挑战，并证明所提出的方法已经回答了之前相关现有方法没有正确或最佳地解决的问题。综述文章应侧重于一种或多种目前已被其他学科广泛使用的统计研究方法，以及应用和对未来方向的讨论。应用说明应至少说明对任何学科的数据挑战创新地应用现有统计方法，并有令人信服的结果。

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英文简介

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.