中文简介

《多元分析杂志》(JMVA)成立于1971年，是出版与多维数据分析和解释有关的新的、相关的方法和特别创新应用的中心场所。该杂志欢迎对多元数据分析和建模的所有方面的贡献，包括聚类分析、判别分析、因子分析和多维连续或离散分布理论。当前感兴趣的主题包括(但不限于)的推理方面介体建模功能数据分析图形化建模高维数据分析图像分析多变量极值理论稀疏的建模空间统计也欢迎对多维响应变量的回归或时间序列分析作出重大贡献的论文。涉及单变量模型的提交，包括具有单个响应变量的回归模型和单变量时间序列模型，被认为不在该期刊的研究范围之内。JMVA对受当代多元数据分析挑战所激励并适合的论文特别感兴趣。方法应该通过标准的数学参数来验证，这些参数可以用渐近参数或基于计算机的实验来补充。当提供清晰的上下文说明和解释时，强烈建议使用带有相关原始数据的插图。内容具有概率论性质或主要贡献于实质领域(例如精算科学、生物统计学、经济学、金融学或水文学)的论文通常不在该期刊的范围之内，只有在使用的统计方法既新颖又广泛适用时才会考虑出版。最后，请注意，多变量生存分析、可靠性理论和统计质量控制的贡献者应该将他们的论文提交给专门研究这些领域的期刊，以确保他们的工作达到目标受众。

投稿网址：http://ees.elsevier.com/jmva/

英文简介

Founded in 1971, the Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly innovative applications pertaining to the analysis and interpretation of multidimensional data.The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including cluster analysis, discriminant analysis, factor analysis, and multidimensional continuous or discrete distribution theory. Topics of current interest include, but are not limited to, inferential aspects ofCopula modelingFunctional data analysisGraphical modelingHigh-dimensional data analysisImage analysisMultivariate extreme-value theorySparse modelingSpatial statisticsPapers making substantial contributions to regression or time series analysis for multidimensional response variables are also invited. Submissions dealing with univariate models, including regression models with a single response variable and univariate time series models, are deemed to fall outside the journal's remit.JMVA is particularly interested in papers motivated by, and fit for, contemporary multivariate data analytic challenges. Methods should be validated through standard mathematical arguments that may be complemented with asymptotic arguments or computer-based experiments. Illustrations with relevant, original data are strongly encouraged when presented with clear contextual justification and explanation.Papers whose content is probabilistic in nature or whose main contribution is to substantive areas (e.g., actuarial science, biosestatistics, economics, finance or hydrology) typically fall outside the journal's scope and will only be considered for publication if the statistical methodology used is both novel and broadly applicable. Finally, note that contributors to multivariate survival analysis, reliability theory and statistical quality control should submit their papers to journals specializing in these areas to ensure that their work reaches the targeted audience.