中文簡介

《多元分析雜志》(JMVA)成立于1971年，是出版與多維數(shù)據(jù)分析和解釋有關(guān)的新的、相關(guān)的方法和特別創(chuàng)新應(yīng)用的中心場所。該雜志歡迎對多元數(shù)據(jù)分析和建模的所有方面的貢獻，包括聚類分析、判別分析、因子分析和多維連續(xù)或離散分布理論。當前感興趣的主題包括(但不限于)的推理方面介體建模功能數(shù)據(jù)分析圖形化建模高維數(shù)據(jù)分析圖像分析多變量極值理論稀疏的建模空間統(tǒng)計也歡迎對多維響應(yīng)變量的回歸或時間序列分析作出重大貢獻的論文。涉及單變量模型的提交，包括具有單個響應(yīng)變量的回歸模型和單變量時間序列模型，被認為不在該期刊的研究范圍之內(nèi)。JMVA對受當代多元數(shù)據(jù)分析挑戰(zhàn)所激勵并適合的論文特別感興趣。方法應(yīng)該通過標準的數(shù)學參數(shù)來驗證，這些參數(shù)可以用漸近參數(shù)或基于計算機的實驗來補充。當提供清晰的上下文說明和解釋時，強烈建議使用帶有相關(guān)原始數(shù)據(jù)的插圖。內(nèi)容具有概率論性質(zhì)或主要貢獻于實質(zhì)領(lǐng)域(例如精算科學、生物統(tǒng)計學、經(jīng)濟學、金融學或水文學)的論文通常不在該期刊的范圍之內(nèi)，只有在使用的統(tǒng)計方法既新穎又廣泛適用時才會考慮出版。最后，請注意，多變量生存分析、可靠性理論和統(tǒng)計質(zhì)量控制的貢獻者應(yīng)該將他們的論文提交給專門研究這些領(lǐng)域的期刊，以確保他們的工作達到目標受眾。

　　英文簡介

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, biostatistics, 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.

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