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ORCIDComputational Statistics & Data Analysis, Volume 125
Volume 125, September 2018
- Shuying Wang, Chunjie Wang, Peijie Wang, Jianguo Sun:
Semiparametric analysis of the additive hazards model with informatively interval-censored failure time data. 1-9 - Jason Cleveland, Weilong Zhao, Wei Wu
:
Robust template estimation for functional data with phase variability using band depth. 10-26 - Sungkyu Jung:
Continuum directions for supervised dimension reduction. 27-43 - Peirong Xu, Heng Peng, Tao Huang:
Unsupervised learning of mixture regression models for longitudinal data. 44-56 - Ville Vuollo, Lasse Holmström:
A scale space approach for exploring structure in spherical data. 57-69 - Md. Ashad Alam, Vince D. Calhoun, Yu-Ping Wang:
Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics. 70-85 - Stijn Luca, Marco A. F. Pimentel, Peter J. Watkinson, David A. Clifton:
Point process models for novelty detection on spatial point patterns and their extremes. 86-103 - Ben Berckmoes, Anna Ivanova, Geert Molenberghs:
On the sample mean after a group sequential trial. 104-118 - Lianqiang Qu, Xinyuan Song, Liuquan Sun:
Identification of local sparsity and variable selection for varying coefficient additive hazards models. 119-135 - Liliana Forzani, Rodrigo García Arancibia, Pamela Llop, Diego Tomassi:
Supervised dimension reduction for ordinal predictors. 136-155 - Scott Marchese, Guoqing Diao:
Joint regression analysis of mixed-type outcome data via efficient scores. 156-170
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