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ORCIDJournal of Multivariate Analysis, Volume 149
Volume 149, July 2016
- Jia Cai, Dao-Hong Xiang
:
Statistical consistency of coefficient-based conditional quantile regression. 1-12 - Thomas Gueuning, Gerda Claeskens:
Confidence intervals for high-dimensional partially linear single-index models. 13-29 - Prathapasinghe Dharmawansa:
Some new results on the eigenvalues of complex non-central Wishart matrices with a rank-1 mean. 30-53 - Wan-Lun Wang, Tsung-I Lin:
Maximum likelihood inference for the multivariate t mixture model. 54-64 - Yan-Yong Zhao, Jin-Guan Lin, Xing-Fang Huang, Hong-Xia Wang:
Adaptive jump-preserving estimates in varying-coefficient models. 65-80 - Yuexiao Dong, Chaozheng Yang, Zhou Yu:
On permutation tests for predictor contribution in sufficient dimension reduction. 81-91 - Ilya Soloveychik, Dmitry Trushin:
Gaussian and robust Kronecker product covariance estimation: Existence and uniqueness. 92-113 - Teng Zhang, Xiuyuan Cheng, Amit Singer:
Marčenko-Pastur law for Tyler's M-estimator. 114-123 - Liuhua Peng, Song Xi Chen, Wen Zhou:
More powerful tests for sparse high-dimensional covariances matrices. 124-143 - Haruhiko Ogasawara:
Bias correction of the Akaike information criterion in factor analysis. 144-159 - Feipeng Zhang, Heng Peng, Yong Zhou:
Composite partial likelihood estimation for length-biased and right-censored data with competing risks. 160-176 - Reinhard Furrer, François Bachoc, Juan Du:
Asymptotic properties of multivariate tapering for estimation and prediction. 177-191 - Yang Li, Zhaojun Wang, Changliang Zou:
A simpler spatial-sign-based two-sample test for high-dimensional data. 192-198 - Yasunori Fujikoshi, Tetsuro Sakurai:
High-dimensional consistency of rank estimation criteria in multivariate linear model. 199-212
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