Computational Statistics & Data Analysis
Comput Stat Data Anal
Computational Statistics & Data Analysis, the official journal of the International Association of Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of three refereed sections, and a fourth section dedicated to news on statistical computing. The refereed sections are divided into the following subject areas:I) Computational Statistics - Manuscripts dealing with the explicit impact of computers on statistical methodology (e.g., algorithms, computer graphics, computer intensive inferential methods, data exploration, evaluation of statistical software, expert systems, neural networks, parallel computing, statistical databases, statistical systems).II) Statistical Methodology for Data Analysis. - Manuscripts dealing with data analysis strategies and methodologies (e.g., classification, data exploration, density estimation, design of experiments, model free data exploration, pattern recognition / image analysis, robust procedures).III)Special Applications - Manuscripts at the interface of statistics and computers (e.g., comparison of statistical methodology, computer-assisted instruction for statistics, simulation experiments). The fourth section, (IV) the Statistical Software Newsletter ("SSN")- The rapid exchange of informational articles and news items (e.g., articles related to the development, usage and validation of statistical software; software reviews; review of books related to computational statistics / data analysis; announcements of new software products / releases; comparison of software products; software tutorials). Announcements and meetings, and news items from the IASC and the ASA Section of Computing and Graphics may also be contributed to this section. Although not peer-reviewed, contributions to the SSN are screened for appropriateness and edited for accuracy.On occasion, special events or topics will be published as a Special Issue of CSDA, prepared by a Guest Editor.
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