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Journal of Multivariate Analysis, Volume 169
Volume 169, January 2019
- Stéphane Gaïffas, Gustaw Matulewicz:
Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process. 1-20 - Wenwen Guo, Hengjian Cui:
Projection tests for high-dimensional spiked covariance matrices. 21-32 - Bin Liu, Cheng Zhou, Xinsheng Zhang:
A tail adaptive approach for change point detection. 33-48 - Ryo Imai, Tatsuya Kubokawa, Malay Ghosh:
Bayesian simultaneous estimation for means in k-sample problems. 49-60 - Tavis Abrahamsen, James P. Hobert:
Fast Monte Carlo Markov chains for Bayesian shrinkage models with random effects. 61-80 - Ricardo Fraiman, Fabrice Gamboa, Leonardo Moreno:
Connecting pairwise geodesic spheres by depth: DCOPS. 81-94 - Ekaterina Bezgina, Marco Burkschat:
On total positivity of exchangeable random variables obtained by symmetrization, with applications to failure-dependent lifetimes. 95-109 - Almut E. D. Veraart:
Modeling, simulation and inference for multivariate time series of counts using trawl processes. 110-129 - Abdelaziz Allam, Tahar Mourid:
Optimal rate for covariance operator estimators of functional autoregressive processes with random coefficients. 130-137 - Lajos Horváth, Gregory Rice:
Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models. 138-165 - Yang Zhou, Di-Rong Chen, Wei Huang:
A class of optimal estimators for the covariance operator in reproducing kernel Hilbert spaces. 166-178 - Xin Lu Tan:
Optimal estimation of slope vector in high-dimensional linear transformation models. 179-204 - Hongmei Lin, Xuejun Jiang, Heng Lian, Weiping Zhang:
Reduced rank modeling for functional regression with functional responses. 205-217 - Xuerong Chen, Haoqi Li, Hua Liang, Huazhen Lin:
Functional response regression analysis. 218-233 - Tonglin Zhang:
General Gaussian estimation. 234-247 - Yury A. Kutoyants:
On parameter estimation of the hidden Ornstein-Uhlenbeck process. 248-263 - Pavel Krupskii, Marc G. Genton:
A copula model for non-Gaussian multivariate spatial data. 264-277 - Irina Gaynanova, Tianying Wang:
Sparse quadratic classification rules via linear dimension reduction. 278-299 - Takeru Matsuda, William E. Strawderman:
Improved loss estimation for a normal mean matrix. 300-311 - Wei Wang, Nan Lin, Xiang Tang:
Robust two-sample test of high-dimensional mean vectors under dependence. 312-329 - Enkelejd Hashorva:
Approximation of some multivariate risk measures for Gaussian risks. 330-340 - Eustasio del Barrio, Paula Gordaliza, Hélène Lescornel, Jean-Michel Loubes:
Central limit theorem and bootstrap procedure for Wasserstein's variations with an application to structural relationships between distributions. 341-362 - Jin Wang:
Asymptotics of generalized depth-based spread processes and applications. 363-380 - Stefan Bedbur, Marcus Johnen, Udo Kamps:
Inference from multiple samples of Weibull sequential order statistics. 381-399 - Samuel Perreault, Thierry Duchesne, Johanna Neslehová:
Detection of block-exchangeable structure in large-scale correlation matrices. 400-422
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