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 of
Copula modeling
Functional data analysis
Graphical modeling
High-dimensional data analysis
Image analysis
Multivariate extreme-value theory
Sparse modeling
Spatial statistics
Papers 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.