Skip to main content
Skip to main menu Skip to spotlight region Skip to secondary region Skip to UGA region Skip to Tertiary region Skip to Quaternary region Skip to unit footer

Slideshow

Zhou Yu

Yu
School of Finance and Statistics, East China Normal University

We propose trace pursuit for model-free variable selection under the sufficient dimension reduction paradigm. Two distinct algorithms are proposed: stepwise trace pursuit and forward trace pursuit, both of which can be combined with many existing sufficient dimension reduction methods. Stepwise trace pursuit achieves selection consistency with fixed dimension p, and is readily applicable in the challenging p>n setting. Forward trace pursuit can serve as an initial screening step to speed up the computation in the case of ultrahigh dimensionality. The screening consistency property of forward trace pursuit based on sliced inverse regression is established. Finite sample performances of trace pursuit and other model-free variable selection methods are compared through numerical studies. This is a joint work with Dr. Yuexiao Dong and Prof. Li-Xing Zhu.

 

More information on Zhou Yu may be found at http://faculty.ecnu.edu.cn/s/1707/main.jspy

Support us

We appreciate your financial support. Your gift is important to us and helps support critical opportunities for students and faculty alike, including lectures, travel support, and any number of educational events that augment the classroom experience. Click here to learn more about giving.

Every dollar given has a direct impact upon our students and faculty.