Some recent statistical learning methods for longitudinal high‐dimensional data-Reference-Cited by-同舟云学术

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Some recent statistical learning methods for longitudinal high‐dimensional data

Published:2013-12-13 Issue:1 Volume:6 Page:10-18
ISSN:1939-5108
Container-title:WIREs Computational Statistics
language:en
Short-container-title:WIREs Comp Stat

Author:

Chen Shuo¹,Grant Edward²,Wu Tong Tong³,Bowman F. DuBois⁴

Affiliation:

1. Department of Epidemiology and Biostatistics University of Maryland College Park MD USA

2. Infectious Disease Clinical Research Program (Henry Jackson Foundation) Uniformed Services University of the Health Sciences Rockville MD USA

3. Department of Biostatistics and Computational Biology University of Rochester Rochester NY USA

4. Department of Biostatistics and Bioinformatics Emory University Atlanta GA USA

Funder

National Science Foundation

Publisher

Wiley

Subject

Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1282

Reference26 articles.

1. Learning to Decode Cognitive States from Brain Images

2. A novel support vector classifier for longitudinal high-dimensional data and its application to neuroimaging data

3. Spline Models for Observational Data

4. 10.1162/153244303322753616

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