Journal of Multivariate Analysis

1971 - 2025

Current editor(s): de Leeuw, J.

From Elsevier
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Volume 185, issue C, 2021

Bayesian multivariate quantile regression using Dependent Dirichlet Process prior

Indrabati Bhattacharya and Subhashis Ghosal

Locally isometric embeddings of quotients of the rotation group modulo finite symmetries

Ralf Hielscher and Laura Lippert

Adaptive function-on-scalar regression with a smoothing elastic net

Ardalan Mirshani and Matthew Reimherr

Exact variance formula for the estimated mean outcome with external intervention based on the front-door criterion in Gaussian linear structural equation models

Hisayoshi Nanmo and Manabu Kuroki

Simultaneous inference for Kendall’s tau

Claus P. Nowak and Frank Konietschke

Kernel density estimation for partial linear multivariate responses models

Jun Zhang, Bingqing Lin and Yan Zhou

Fast implementation of partial least squares for function-on-function regression

Zhiyang Zhou

Dependence structure estimation using Copula Recursive Trees

Oskar Laverny, Esterina Masiello, Véronique Maume-Deschamps and Didier Rulliere

Robust estimation for Binomial conditionally nonlinear autoregressive time series based on multivariate conditional frequencies

Yuriy Kharin and Valeriy Voloshko

Testing the equality of a large number of means of functional data

M. Dolores Jiménez-Gamero and Alba M. Franco-Pereira

Clustering by principal component analysis with Gaussian kernel in high-dimension, low-sample-size settings

Yugo Nakayama, Kazuyoshi Yata and Makoto Aoshima

A formulation for continuous mixtures of multivariate normal distributions

Reinaldo B. Arellano-Valle and Adelchi Azzalini

Eigenvector-based sparse canonical correlation analysis: Fast computation for estimation of multiple canonical vectors

Wenjia Wang and Yi-Hui Zhou

ℓ2,0-norm based selection and estimation for multivariate generalized linear models

Yang Chen, Ziyan Luo and Lingchen Kong

Asymptotic properties of Bernstein estimators on the simplex

Frédéric Ouimet

Volume 184, issue C, 2021

Depth-based classification for relational data with multiple attributes

Xu Zhang, Yahui Tian, Guoyu Guan and Yulia R. Gel

Projection theorems and estimating equations for power-law models

Atin Gayen and M. Ashok Kumar

A geometric investigation into the tail dependence of vine copulas

Emma S. Simpson, Jennifer L. Wadsworth and Jonathan A. Tawn

Heckman selection-t model: Parameter estimation via the EM-algorithm

Victor H. Lachos, Marcos O. Prates and Dipak K. Dey

A topologically valid construction of depth for functional data

Alicia Nieto-Reyes and Heather Battey

Estimation and optimal structure selection of high-dimensional Toeplitz covariance matrix

Yihe Yang, Jie Zhou and Jianxin Pan

An association test for functional data based on Kendall’s Tau

Sneha Jadhav and Shuangge Ma

A new general class of RC association models: Estimation and main properties

Antonio Forcina and Maria Kateri

Limiting laws for extreme eigenvalues of large-dimensional spiked Fisher matrices with a divergent number of spikes

Junshan Xie, Yicheng Zeng and Lixing Zhu

Distance-based tests for planar shape

Wenia Valdevino Félix de Lima, Abraão David Costa do Nascimento and Getúlio José Amorim do Amaral

Minimum Average Variance Estimation with group Lasso for the multivariate response Central Mean Subspace

Hong-Fan Zhang

Principal loading analysis

Jan O. Bauer and Bernhard Drabant

On classification with nonignorable missing data

Majid Mojirsheibani

Kick-one-out-based variable selection method for Euclidean distance-based classifier in high-dimensional settings

Tomoyuki Nakagawa, Hiroki Watanabe and Masashi Hyodo

Expectile depth: Theory and computation for bivariate datasets

Ignacio Cascos and Maicol Ochoa

Semi-parametric estimation of multivariate extreme expectiles

Nicholas Beck, Elena Di Bernardino and Mélina Mailhot

Inference in high dimensional linear measurement error models

Mengyan Li, Runze Li and Yanyuan Ma

Stochastic decomposition for ℓp-norm symmetric survival functions on the positive orthant

Jan-Frederik Mai and Ruodu Wang

On the asymptotic normality and efficiency of Kronecker envelope principal component analysis

Shih-Hao Huang and Su-Yun Huang

A high dimensional nonparametric test for proportional covariance matrices

Kai Xu, Yan Tian and Daojiang He

Volume 183, issue C, 2021

Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach

Yongli Zhang, Craig Rolling and Yuhong Yang

Subspace rotations for high-dimensional outlier detection

Hee Cheol Chung and Jeongyoun Ahn

Heterogeneous hypergeometric functions with two matrix arguments and the exact distribution of the largest eigenvalue of a singular beta-Wishart matrix

Koki Shimizu and Hiroki Hashiguchi

Canonical correlation analysis for elliptical copulas

Benjamin W. Langworthy, Rebecca L. Stephens, John H. Gilmore and Jason P. Fine

Joint mean–covariance estimation via the horseshoe

Yunfan Li, Jyotishka Datta, Bruce A. Craig and Anindya Bhadra

Shrinkage estimation with singular priors and an application to small area estimation

Ryumei Nakada, Tatsuya Kubokawa, Malay Ghosh and Sayar Karmakar

Reconstruction of atomic measures from their halfspace depth

Petra Laketa and Stanislav Nagy

Compound vectors of subordinators and their associated positive Lévy copulas

Alan Riva-Palacio and Fabrizio Leisen

A non-recursive formula for various moments of the multivariate normal distribution with sectional truncation

Haruhiko Ogasawara

Asymptotic properties on high-dimensional multivariate regression M-estimation

Hao Ding, Shanshan Qin, Yuehua Wu and Yaohua Wu

Generalized Schott type tests for complete independence in high dimensions

Daojiang He, Huanyu Liu, Kai Xu and Mingxiang Cao

Variable selection for partially linear models via Bayesian subset modeling with diffusing prior

Jia Wang, Xizhen Cai and Runze Li

Semiparametric method and theory for continuously indexed spatio-temporal processes

Jialuo Liu, Tingjin Chu, Jun Zhu and Haonan Wang

Volume 182, issue C, 2021

Dynamic tilted current correlation for high dimensional variable screening

Bangxin Zhao, Xin Liu, Wenqing He and Grace Y. Yi

Widening the scope of an eigenvector stochastic approximation process and application to streaming PCA and related methods

Jean-Marie Monnez and Abderrahman Skiredj

Analysis of the rate of convergence of fully connected deep neural network regression estimates with smooth activation function

Sophie Langer

Approximating smooth functions by deep neural networks with sigmoid activation function

Sophie Langer

On the behavior of the DFA and DCCA in trend-stationary processes

Taiane Schaedler Prass and Guilherme Pumi

On the specification of multivariate association measures and their behaviour with increasing dimension

Irène Gijbels, Vojtěch Kika and Marek Omelka

Testing multivariate quantile by empirical likelihood

Xuejun Ma, Shaochen Wang and Wang Zhou

On the copula correlation ratio and its generalization

Jia-Han Shih and Takeshi Emura

Ordering results for elliptical distributions with applications to risk bounds

Jonathan Ansari and Ludger Rüschendorf

Testing independence of functional variables by angle covariance

Tingyu Lai, Zhongzhan Zhang, Yafei Wang and Linglong Kong

Optimal designs for mixed continuous and binary responses with quantitative and qualitative factors

Ming-Hung Kao and Hazar Khogeer