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期刊名称：BAYESIAN ANALYSIS ISSN： 1931-6690 出版频率： Irregular 出版社： INT SOC BAYESIAN ANALYSIS, CARNEGIE MELLON UNIV, DEPT STTISTICS, PITTSBURGH, USA, PA, 15213   出版社网址： http://ba.stat.cmu.edu/ 期刊网址： http://ba.stat.cmu.edu/ 影响因子： 3.728 主题范畴： MATHEMATICS, INTERDISCIPLINARY APPLICATIONS;    STATISTICS & PROBABILITY 期刊简介(About the journal)    投稿须知(Instructions to Authors)    编辑部信息(Editorial Board)    About the journal Bayesian Analysis is an electronic journal of the International Society for Bayesian Analysis. It seeks to publish a wide range of articles that demonstrate or discuss Bayesian methods in some theoretical or applied context. The journal welcomes submissions involving presentation of new computational and statistical methods; reviews, criticism, and discussion of existing approaches; historical perspectives; description of important scientific or policy application areas; case studies; and methods for experimental design, data collection, data sharing, or data mining. Evaluation of submissions will be based on importance of content and effectiveness of communication. Some general stylistic recommendations are provided via the Submit or Resubmit web page. Bayesian Analysis is dedicated to prompt review and publication of manuscripts.   Now indexed by Science Citation Index - Expanded (SCIE), including the Web of Science (In the 2009 Journal Citation Reports, Bayesian Analysis has an impact factor of 0.968 and a 5-year impact factor of 3.083 which ranks it 8th out of 100 probability and statistics journals, and it ranks 6th on Article Influence Score) Instructions to Authors An over-riding concern is to make effective use of the electronic medium. Papers should be split into two distinct parts: a main manuscript and supplementary material. The main manuscript should be as succinct and readable as possible; the supplementary material can be any length (and in some cases may be unnecessary). The supplementary material may contain additional figures and tables, details about data, mathematical derivations, further explanations, or additional simulations or other supporting studies. The supplementary material should be placed after the main manuscript and before the references. Keeping the pieces distinct will allow someone to download the main manuscript without the supplementary material---but a serious student of the subject would want both. Main manuscripts should contain those parts that authors believe to be essential for all readers. Authors should keep in mind that readership is likely to be increased when the main manuscript is kept short.   Figures should be used to help with exposition. Where possible, one or more figures should provide illustrations of main results. Figures should be integrated with the text if possible, rather than appearing at the end. These figures may be split into multiple parts. The legends on these figures should have enough detail that someone can get an impression of what is being displayed just by looking at the figures. (Explanations of how to read figures should appear in the legend rather than in the main text.) In most cases the legends should articulate the actual findings rather than simply identifying which figure is which. All relevant units should be identified, preferably on the axes (and color or gray scales). Extraneous axis labels and headings usually should be avoided unless they are large enough to be read easily and clear enough to be understood without effort. An often-preferable alternative is to explain the plots more fully in the legend. Color should be used in figures only where absolutely necessary, since the print version of the journal is in black and white (though color will still be apparent in the online version).   Abstracts should include a brief summary of the main research findings. Generic statements such as "an example is presented" should be avoided. Instead, minimal details about examples should be included, as in "we illustrate the benefit of our approach by analyzing data from a rocket science experiment to provide improved estimates of escape velocity".   Case studies should make sure to highlight both the main results for the scientific, technological, or policy application and also the main points of interest to a statistician working in a different field. The latter are often appropriate for a concluding section.   Concluding summaries should be provided only in the context of giving additional perspective on the work. Editorial Board Editors Ming-Hui Chen, University of Connecticut Kate Cowles, University of Iowa David Dunson, Duke University David Heckerman, Microsoft Corp. Michael Jordan, University of California - Berkeley Antonietta Mira, University of Insubria Sonia Petrone, Universita Bocconi Fabrizio Ruggeri, CNR - IMATI (Milano) Bruno Sanso, University of California - Santa Cruz Mark Steel, University of Warwick Kert Viele, University of Kentucky Editor-in-Chief Herbie Lee, University of California - Santa Cruz System Managing Editor Pantelis Vlachos, Merck Serono Managing Editor Alyson Wilson, Iowa State University Production Editor Angelika van der Linde, Universitat Bremen Editorial Assistant Heidi Sestrich, Carnegie Mellon University Associate Editors Former Editors