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ORCIDJournal of Multivariate Analysis, Volume 161
Volume 161, September 2017
- Xinbing Kong, Zhi Liu
, Peng Zhao, Wang Zhou:
SURE estimates under dependence and heteroscedasticity. 1-11 - Nicolas Goix, Anne Sabourin, Stéphan Clémençon:
Sparse representation of multivariate extremes with applications to anomaly detection. 12-31 - Nathalie Akakpo:
Multivariate intensity estimation via hyperbolic wavelet selection. 32-57 - Dário Ferreira, Sandra S. Ferreira, Célia Nunes, Miguel Fonseca, Adilson Da Silva, João T. Mexia:
Estimation and incommutativity in mixed models. 58-67 - Hui Ding, Yanghui Liu, Wenchao Xu, Riquan Zhang:
A class of functional partially linear single-index models. 68-82 - Enakshi Saha, Soham Sarkar, Anil Kumar Ghosh:
Some high-dimensional one-sample tests based on functions of interpoint distances. 83-95 - Guillaume Carlier, Victor Chernozhukov, Alfred Galichon:
Vector quantile regression beyond the specified case. 96-102 - Toshio Honda, Ryota Yabe:
Variable selection and structure identification for varying coefficient Cox models. 103-122 - Alexandra Soberón, Winfried Stute:
Assessing skewness, kurtosis and normality in linear mixed models. 123-140 - Paula M. Murray, Ryan P. Browne, Paul D. McNicholas:
Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering. 141-156 - Wan-Lun Wang, Luis Mauricio Castro, Tsung-I Lin:
Automated learning of t factor analysis models with complete and incomplete data. 157-171 - Kei Hirose, Hironori Fujisawa, Jun Sese:
Robust sparse Gaussian graphical modeling. 172-190 - Trambak Banerjee, Gourab Mukherjee, Peter Radchenko:
Feature screening in large scale cluster analysis. 191-212
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