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Seminar Announcement


Density estimation for incomplete data model

Ao Yuan

National Human Genome Center

Howard University

Engr 4201 (Computer science conference room)  

4400 University Drive, Fairfax, VA 22030

Time: 11:00 A.M. - 12:00 P.M.

Date: Friday, Mar 8, 2013 

Abstract

For incomplete data model, the commonly used density estimator of the underlying distribution cannot be computed directly, as the corresponding kernel requires all original data to be available. To estimate density function with such incomplete data model using only the observed data, we propose to use a conditional version of the kernel given the observed data. We study such kernel density estimator for several commonly used incomplete data models.  Some large-sample properties of the proposed estimators are investigated.



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Yunpeng Zhao, PhD

Assistant Professor
Department of Statistics
Volgenau School of Engineering
George Mason University
Engineering Building, Room 1719, MS 4A7
4400 University Drive
Fairfax, VA 22030-4444
 
Phone: 703-993-1674
Email: [log in to unmask]