Journal of Multivariate Analysis

1971 - 2025

Current editor(s): de Leeuw, J.

From Elsevier
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Volume 156, issue C, 2017

A statistical framework for pathway and gene identification from integrative analysis pp. 1-17

Quefeng Li, Menggang Yu and Sijian Wang

Bayesian prediction with multiple-samples information pp. 18-28

Federico Camerlenghi, Antonio Lijoi and Igor Prünster

Distribution-free detection of a submatrix pp. 29-38

Ery Arias-Castro and Yuchao Liu

Regularized partially functional quantile regression pp. 39-56

Fang Yao, Shivon Sue-Chee and Fan Wang

Moderate deviation principles for classical likelihood ratio tests of high-dimensional normal distributions pp. 57-69

Hui Jiang and Shaochen Wang

High-dimensional tests for functional networks of brain anatomic regions pp. 70-88

Jichun Xie and Jian Kang

Semi-parametric order-based generalized multivariate regression pp. 89-102

Milad Kharratzadeh and Mark Coates

On local linear regression for strongly mixing random fields pp. 103-115

Mohamed El Machkouri, Khalifa Es-Sebaiy and Idir Ouassou

Estimation and model identification of longitudinal data time-varying nonparametric models pp. 116-136

Shu Liu, Jinhong You and Heng Lian

Volume 155, issue C, 2017

Weak convergence of multivariate partial maxima processes pp. 1-11

Danijel Krizmanić

Asymptotic properties of a component-wise ARH(1) plug-in predictor pp. 12-34

J. Álvarez-Liébana, D. Bosq and M.D. Ruiz-Medina

The empirical beta copula pp. 35-51

Johan Segers, Masaaki Sibuya and Hideatsu Tsukahara

Properties of extremal dependence models built on bivariate max-linearity pp. 52-71

Mónika Kereszturi and Jonathan Tawn

Testing proportionality between the first-order intensity functions of spatial point processes pp. 72-82

Tonglin Zhang and Run Zhuang

Simultaneous confidence bands for contrasts between several nonlinear regression curves pp. 83-104

Xiaolei Lu and Satoshi Kuriki

Monitoring multivariate time series pp. 105-121

Yannick Hoga

Some asymptotic theory for Silverman’s smoothed functional principal components in an abstract Hilbert space pp. 122-132

Gamage Pemantha Lakraj and Frits Ruymgaart

Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models pp. 133-150

Yujie Li, Gaorong Li, Heng Lian and Tiejun Tong

Expected predictive least squares for model selection in covariance structures pp. 151-164

Haruhiko Ogasawara

Smooth predictive model fitting in regression pp. 165-179

Prabir Burman and Debashis Paul

Stationary Gaussian Markov processes as limits of stationary autoregressive time series pp. 180-186

Philip A. Ernst, Lawrence D. Brown, Larry Shepp and Robert L. Wolpert

Efficient dimension reduction for multivariate response data pp. 187-199

Yaowu Zhang, Liping Zhu and Yanyuan Ma

Linear hypothesis testing in high-dimensional one-way MANOVA pp. 200-216

Jin-Ting Zhang, Jia Guo and Bu Zhou

High-dimensional rank tests for sphericity pp. 217-233

Long Feng and Binghui Liu

A natural parametrization of multivariate distributions with limited memory pp. 234-251

Natalia Shenkman

An innovations algorithm for the prediction of functional linear processes pp. 252-271

J. Klepsch and C. Klüppelberg

Wishart distributions: Advances in theory with Bayesian application pp. 272-283

Andriëtte Bekker, Janet van Niekerk and Mohammad Arashi

Optimal Berry–Esseen bound for statistical estimations and its application to SPDE pp. 284-304

Yoon Tae Kim and Hyun Suk Park

Testing block-diagonal covariance structure for high-dimensional data under non-normality pp. 305-316

Yuki Yamada, Masashi Hyodo and Takahiro Nishiyama

Multivariate dependence modeling based on comonotonic factors pp. 317-333

Lei Hua and Harry Joe

Multiple quantile regression analysis of longitudinal data: Heteroscedasticity and efficient estimation pp. 334-343

Hyunkeun Cho, Seonjin Kim and Mi-Ok Kim

Change-point detection and bootstrap for Hilbert space valued random fields pp. 344-368

Béatrice Bucchia and Martin Wendler

Volume 154, issue C, 2017

Sparse clustering of functional data pp. 1-18

Davide Floriello and Valeria Vitelli

Distance correlation coefficients for Lancaster distributions pp. 19-39

Johannes Dueck, Dominic Edelmann and Donald Richards

Quantile index coefficient model with variable selection pp. 40-58

Weihua Zhao and Heng Lian

Robust estimators in semi-functional partial linear regression models pp. 59-84

Graciela Boente and Alejandra Vahnovan

An offspring of multivariate extreme value theory: The max-characteristic function pp. 85-95

Michael Falk and Gilles Stupfler

Improved estimation of fixed effects panel data partially linear models with heteroscedastic errors pp. 96-111

Jianhua Hu, Jinhong You and Xian Zhou

Nonparametric estimation of a latent variable model pp. 112-134

Augustin Kelava, Michael Kohler, Adam Krzyżak and Tim Fabian Schaffland

Functional Cramér–Rao bounds and Stein estimators in Sobolev spaces, for Brownian motion and Cox processes pp. 135-146

Eni Musta, Maurizio Pratelli and Dario Trevisan

Improved model checking methods for parametric models with responses missing at random pp. 147-161

Zhihua Sun, Feifei Chen, Xiaohua Zhou and Qingzhao Zhang

Parametrizations, fixed and random effects pp. 162-176

Azzouz Dermoune and Cristian Preda

Hotelling’s T2 tests in paired and independent survey samples: An efficiency comparison pp. 177-198

Ludwig Baringhaus and Daniel Gaigall

Gaussian tree constraints applied to acoustic linguistic functional data pp. 199-215

Nathaniel Shiers, John A.D. Aston, Jim Q. Smith and John S. Coleman

Calibration tests for multivariate Gaussian forecasts pp. 216-233

Wei Wei, Fadoua Balabdaoui and Leonhard Held

Bayesian regularized quantile structural equation models pp. 234-248

Xiang-Nan Feng, Yifan Wang, Bin Lu and Xin-Yuan Song

Density ratio model for multivariate outcomes pp. 249-261

Scott Marchese and Guoqing Diao

Semi-parametric inference for semi-varying coefficient panel data model with individual effects pp. 262-281

Xuemei Hu

On the CLT for discrete Fourier transforms of functional time series pp. 282-295

Clément Cerovecki and Siegfried Hörmann

Volume 153, issue C, 2017

On the classification problem for Poisson point processes pp. 1-15

Alejandro Cholaquidis, Liliana Forzani, Pamela Llop and Leonardo Moreno

An equation-by-equation estimator of a multivariate log-GARCH-X model of financial returns pp. 16-32

Christian Francq and Genaro Sucarrat

A bivariate failure time model with random shocks and mixed effects pp. 33-51

Sophie Mercier and Hai Ha Pham

Bayesian estimators in uncertain nested error regression models pp. 52-63

Shonosuke Sugasawa and Tatsuya Kubokawa

Scale and curvature effects in principal geodesic analysis pp. 64-82

Drew Lazar and Lizhen Lin

Signal extraction approach for sparse multivariate response regression pp. 83-97

Ruiyan Luo and Xin Qi

Third-order average local powers of Bartlett-type adjusted tests: Ordinary versus adjusted profile likelihood pp. 98-120

Yoshihide Kakizawa

Nonparametric estimation of the distribution of the autoregressive coefficient from panel random-coefficient AR(1) data pp. 121-135

Remigijus Leipus, Anne Philippe, Vytautė Pilipauskaitė and Donatas Surgailis

Mean vector testing for high-dimensional dependent observations pp. 136-155

Deepak Nag Ayyala, Junyong Park and Anindya Roy

Spectral covariance and limit theorems for random fields with infinite variance pp. 156-175

Julius Damarackas and Vygantas Paulauskas

Data-driven kNN estimation in nonparametric functional data analysis pp. 176-188

Lydia-Zaitri Kara, Ali Laksaci, Mustapha Rachdi and Philippe Vieu

Multivariate nonparametric test of independence pp. 189-210

Yanan Fan, Pierre Lafaye de Micheaux, Spiridon Penev and Donna Salopek

Penalized spline estimation in the partially linear model pp. 211-235

Ashley D. Holland

A link-free approach for testing common indices for three or more multi-index models pp. 236-245

Xuejing Liu, Lei Huo, Xuerong Meggie Wen and Robert Paige

Admissibility of linear estimators of the common mean parameter in general linear models under a balanced loss function pp. 246-254

Ming-Xiang Cao and Dao-Jiang He

Permuting longitudinal data in spite of the dependencies pp. 255-265

Sarah Friedrich, Edgar Brunner and Markus Pauly