Computational Statistics & Data Analysis

Journal Title：Computational Statistics & Data Analysis

Computational Statistics and Data Analysis (CSDA), an Official Publication of the network Computational and Methodological Statistics (CMStatistics) and of the International Association for 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 four refereed sections which are divided into the following subject areas:

I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics,computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article.

II) Statistical Methodology for Data Analysis - Manuscripts dealing with novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures.

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III) Special Applications - [...]

IV) Annals of Statistical Data Science [...]

计算统计与数据分析 (CSDA) 是计算与方法统计网络 (CMStatistics) 和国际统计计算协会 (IASC) 的官方出版物，是一本致力于传播计算统计和数据分析领域的方法研究和应用的国际期刊。该期刊由四个评审部分组成，分为以下主题领域：

I) 计算统计 - 涉及以下内容的稿件：1) 计算机对统计方法的明确影响（例如，贝叶斯计算、生物信息学、计算机图形学、计算机密集型推理方法、数据探索、数据挖掘、专家系统、启发式、基于知识的系统、机器学习、神经网络、数值和优化方法、并行计算、统计数据库、统计系统），以及 2) 统计软件和算法的开发、评估和验证。软件和算法可以与稿件一起提交，并与在线文章一起存储。

II）数据分析的统计方法 - 涉及生物统计学（临床试验、流行病学研究、统计遗传学或遗传/环境相互作用的设计和分析方法）、化学计量学、分类、数据探索、密度估计、实验设计、环境计量学、教育、图像分析、营销、无模型数据探索、模式识别、心理测量学、统计物理、图像处理、稳健程序的新颖和原创数据分析策略和方法的稿件。

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III）特殊应用 - [...]

IV）统计数据科学年鉴 [...]

Computational Statistics & Data Analysis创刊于1983年，由Elsevier出版商出版，收稿方向涵盖数学 - 计算机：跨学科应用全领域，此刊是中等级别的SCI期刊，所以过审相对来讲不是特别难，但是该刊专业认可度不错，仍然是一本值得选择的SCI期刊 。平均审稿速度 较快,2-4周 ，影响因子指数1.5，该期刊近期没有被列入国际期刊预警名单，广大学者值得一试。