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Journal of Multivariate Analysis
基本信息
期刊名称 Journal of Multivariate Analysis
J MULTIVARIATE ANAL
期刊ISSN 0047-259X
期刊官方网站 https://www.sciencedirect.com/journal/journal-of-multivariate-analysis
是否OA No
出版商 Academic Press Inc.
出版周期 Monthly
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始发年份 1971
年文章数 75
影响因子 1.4(2023)  scijournal影响因子  greensci影响因子
中科院SCI期刊分区
大类学科 小类学科 Top 综述
数学3区 STATISTICS & PROBABILITY 统计学与概率论4区
CiteScore
CiteScore排名 CiteScore SJR SNIP
学科 排名 百分位 2.4 0.837 1.169
Mathematics
Numerical Analysis
35/88 60%
Mathematics
Statistics and Probability
112/278 59%
Decision Sciences
Statistics, Probability and Uncertainty
73/168 56%
补充信息
自引率 7.1%
H-index 66
SCI收录状况 Science Citation Index Expanded
官方审稿时间 登录后查看
网友分享审稿时间 数据统计中,敬请期待。
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PubMed Central (PMC) http://www.ncbi.nlm.nih.gov/nlmcatalog?term=0047-259X%5BISSN%5D
投稿指南
期刊投稿网址 https://www.editorialmanager.com/JMVA
收稿范围
The Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly theoretical developments of multivariate statistics combined with innovative applications pertaining to the analysis and interpretation of multidimensional data.
Papers making substantial contributions to regression or time series analysis for multidimensional response variables are invited.

Please note that a JMVA article is of length 15-25 pages. All proofs of propositions, theorems and lemmas should appear in the main body of the text or in an appendix (not in supplement).

The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including:
cluster analysis, discriminant analysis, factor analysis, independent component analysis and multidimensional continuous or discrete distribution theory, where the theory should connect to multivariate statistical inference.


Topics of current interest include, but are not limited to, inferential aspects of:
Change point analysis
Copula modeling
Functional data analysis
Graphical modeling
High-dimensional data analysis
Image analysis
Multivariate extreme-value theory
Multivariate mixed models.
Sparse modeling
Spatial statistics


Submissions dealing with univariate models, including regression models with a single response variable and univariate time series models, are usually deemed to fall outside the journal's remit.

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.

This journal has an Open Archive. All published items, including research articles, have unrestricted access and will remain permanently free to read and download 48 months after publication. All papers in the Archive are subject to Elsevier's user license.
收录体裁
投稿指南 https://www.sciencedirect.com/journal/journal-of-multivariate-analysis/publish/guide-for-authors
投稿模板
参考文献格式 https://www.elsevier.com/journals/journal-of-multivariate-analysis/0047-259x/guide-for-authors
编辑信息
Editor-in-Chief

Dietrich von Rosen

Swedish University of Agricultural Sciences, Uppsala, Sweden
Executive Editor

Tonu Kollo

University of Tartu, Tartu, Estonia
Associate Editors

Makoto Aoshima

University of Tsukuba Graduate School of Pure and Applied Sciences Doctoral Program in Mathematics, Tsukuba, Japan Classification and discrimination methods; High-dimensional data analysis; Principal component analysis

Adelchi Azzalini

University of Padua, Padova, Italy Density-based non-parametric cluster analysis; Likelihood-based inference; Longitudinal data analysis; Multivariate distribution theory; Non-parametric estimation via smoothing methods

Taras Bodnar

Stockholm University, Stockholm, Sweden Bayesian statistics, Copula modeling, High-dimensional statistics, Multiple testing

Prabir Burman

University of California Davis, Davis, California, United States Asymptotic theory, Discrete data, Nonparametric function estimation, Resampling methods, Spatial statistics, Spatio-temporal statistics, Time series

Kehui Chen

University of Pittsburgh, Pittsburgh, Pennsylvania, United States Functional and longitudinal data analysis, Multilevel clustering,Multilevel correlation analysis, Network analysis,Applications in brain functional connectivity

Ratan Dasgupta

Indian Statistical Institute, Kolkata, India Advanced applied multivariate analysis

Liliana Forzani

National University of the Littoral Faculty of Chemical Engineering, Sante Fe, ArgentinaCasual inference; High-dimensional data analysis; Multivariate linear models; Multivariate generalized linear models; Sufficient dimension reduction

Christian Genest

McGill University, Montréal, Quebec, Canada Copula modeling, Extreme-value theory, Multivariate distributions, Rank-based inference

Stéphane Girard

Inria Research Centre Grenoble Rhône-Alpes, Montbonnot St Martin, FranceClassification and discrimination methods; Copulas; Extreme value inference; High-dimensional data analysis

Solomon Harrar

University of Kentucky, Lexington, Kentucky, United States Asymptotic theory; High-dimensional data analysis; Multivariate distribution theory; Rank based methods

Thomas Holgersson

Linnaeus University Department of Economics and Statistics, Växjö, Sweden Descriptive multivariate analysis; High-dimensional data analysis; Regularization methods; Multivariate autokorrelation

Jianhua Hu

Shanghai University of Finance and Economics, Shanghai, China Compositional data analysis; High-dimensional data analysis; Sparse statistical modelling; Spatial statistics

Jianhua Huang

Texas A&M University College Station, College Station, Texas, United States Functional data analysis; Graphical models; High-dimensional data analysis; Sparse statistical modelling; Spatial statistics

Harry Joe

The University of British Columbia, Vancouver, British Columbia, Canada Composite likelihood; Copulas; Dependence measures; Extreme value inference; Latent variable models; Multivariate random effects models.

John Kent

University of Leeds, Leeds, United Kingdom Directional statistics; Shape analysis

Yuriy Kharin

Belarusian State University, Minsk, Belarus Classification and discrimination methods; Robust multivariate methods

Bernhard Klar

Helmholtz Nuclear Research Centre Karlsruhe, Karlsruhe, Germany Classification and discrimination methods; Copulas; Multivariate distribution theory

Ivan Kojadinovic

University of Pau and Pays de l’Adour, Pau, France Copulas, Change-point detection, Resampling techniques, Empirical processes, Non-parametric multivariate analysis, Environmental and financial applications

Piotr Kokoszka

Colorado State University, Fort Collins, Colorado, United States Extreme value inference; Functional data analysis; Spatial statistics

Runze Li

Pennsylvania State University, University Park, Pennsylvania, United States Feature screening methods; High-dimensional data analysis; Longitudinal data analysis

Yehua Li

University of California Riverside, Riverside, California, United States Functional data analysis; High-dimensional data analysis; Longitudinal data analysis, Spatial-temporal statistics

Shuangzhe Liu

University of Canberra Faculty of Education Science and Technology Multivariate distributions; multivariate linear models and GLM; statistical diagnostics

Yufeng Liu

University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United StatesClassification and discrimantion methods; Clustering methods; Graphical models; High-dimensional data analysis; Individualized decision rules; Sparse statistical modelling

Richard Lockhart

Simon Fraser University, Burnaby, British Columbia, Canada

Eric Marchand

University of Sherbrooke, Sherbrooke, Quebec, Canada Bayesian methods; Estimation with constraints; Multivariate distribution theory; Parametric inference; Stein estimation

Thomas Mathew

University of Maryland Baltimore, Baltimore, Maryland, United States General multivariate statistical analysis; Mixed and random effects models

Paul McNicholas

McMaster University, Hamilton, Ontario, Canada

Alexander Meister

University of Rostock, Rostock, Germany Functional data analysis, Non-parametric curve estimation, Le Cam theory of statistical experiments, Statistical inverse problems

Sayan Mukherjee

Duke University, Durham, North Carolina, United States Bayesian methods, Geometry and topology in statistical inference, Statistical genetics, Statistical machine learning

Jamal Najim

University Paris-Est Créteil Val de Marne, Creteil, France High-dimensional data analysis; Large random matrix theory

Johanna G. Nešlehová

McGill University, Montréal, Quebec, Canada Copula modeling, Extreme-value theory, Multivariate distributions, Rank-based inference

Natalie Neumeyer

University of Hamburg, Hamburg, Germany Multivariate bootstrap methods; Non-parametric multivariate analysis; Semi-parametric multivariate analysis.

Klaus Nordhausen

TU Wien University, Wien, Austria Blind source separation methods; Dimension reduction; Robust multivariate methods

Haruhiko Ogasawara

Otaru University of Commerce, Otaru, Japan Asymptotic theory; Factor analysis; Multivariate skewness and kurtosis measures; Principal component analysis

Jianxin Pan

The University of Manchester, Manchester, United Kingdom Classification and discrimination methods; High-dimensional data analysis; Network analysis; Multivariate distributions; Patterned covariance matrix analysis

Leandro Pardo

Complutense University of Madrid, Madrid, Spain Analysis of multi-way tables; Asymptotic theory; Minimum distance estimators; Robust multivariate methods

Junyong Park

University of Baltimore, Baltimore, Maryland, United States Classification and discrimination methods; Clustering methods; Hypotheses testing in high dimensions; Multiple comparisons.

Wolfgang Polonik

University of California Davis, Davis, California, United States Non-parametric multivariate analysis; Network Analysis; Shape constrained inference; Topological data analysis

Jörg Polzehl

Weierstrass Institute for Applied Analysis and Stochastics, Berlin, GermanyComputational statistics, Functional data analysis, Neuroimaging, Sparse modelling

Matthew Reimherr

Pennsylvania State University, University Park, Pennsylvania, United States Applications in genetics and public health; Functional data analysis, High-dimensional data analysis, Longitudinal data analysis, Nonparametric regression, Shape analysis

Anne Ruiz-Gazen

Toulouse School of Economics, Toulouse, France Computational statistics; Covariance estimation; Outlier detection; Robust statistics; Survey sampling

Wolfgang Schmid

European University Viadrina

Takashi Seo

Tokyo University of Science, Tokyo, Japan Asymptotic theory; Missing data analysis; Multivariate distribution theory

Ali Shojaei

University of Washington, Seattle, Washington, United States Graphical models; Analysis of time series and panel data; High-dimensional data analysis; Network analysis; Statistical aspects of machine learning

Peter X.K. Song

University of Michigan, Ann Arbor, Michigan, United States Dependence modeling, Estimating functions, High-dimensional data analysis, Longitudinal data analysis, Meta analysis

Akimichi Takemura

Shiga University, Hikone, Japan Algebraic methods in multivariate analysis; Decision theory; Multivariate distribution theory

Thomas Verdebout

ULB, Bruxelles, Belgium Asymptotic theory; Directional statistics; High-dimensional data analysis; Rank based multivariate methods

Marlos Viana

University of Illinois at Chicago, Chicago, Illinois, United States Combined multivariate analysis; Complex multivariate analysis; Symmetry analysis of multivariate data.

Philippe Vieu

Paul Sabatier University, Toulouse, France Functional data analysis; Non-parametric multivariate analysis; Semi-parametric multivariate analysis; Sparse statistical modelling

Julia Volaufova

Louisiana State University Health Sciences Center Human Development Center, New Orleans, Louisiana, United States Longitudinal data analysis; Mixed and random effects models; Multivariate linear models

Jianfeng Yao

University of Hong Kong, Pokfulam, Hong Kong High-dimensional data analysis; Large sample covariance matrices; Random matrix theory

Xianyang Zhang

Texas A&M University System, College Station, Texas, United States High dimensional data analysis, Mutlivariate time series analysis

Shurong Zheng

Northeast Normal University, Changchun, China Constrained statistical inference, High dimensional tests, Large dimensional random matrix theory

Liping Zhu

Renmin University of China, Beijing, China Dependence measures; Dimension reduction; Feature screening

Konstantinos Zografos

University of Ioannina, Ioannina, Greece Classification and discrimination methods; Copulas; Discrete multivariate methods; Dependence measures; Multivariate distribution theory; Statistical distances
Advisory Board

H. Chernoff

Harvard University, Cambridge, Massachusetts, United States

D.R. Cox

University of Oxford, Oxford, United Kingdom

D.A.S. Fraser

University of Toronto, Toronto, Ontario, Canada

C. Genest

McGill University, Montréal, Quebec, Canada

C.R. Rao

Pennsylvania State University, University Park, Pennsylvania, United States
Founded and Edited by

P.R. Krishnaiah

1971 - 1988
Chief Editors

C.R. Rao

1988 - 1992

B.C. Arnold

1993 - 1997

J. de Leeuw

1998-2015

C. Genest

2015 - 2019
Publisher

D. Sugrue


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