SEMINARS
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Spring 2006
STATISTICS
COLLOQUIUM
Wednesday, March 7, 2007
3:30-4:00—Refreshments
4:00-5:00—Talk
Yost Hall, Room 101
Bin Wang, PhD
Department of Mathematics and Statistics
University of South Alabama
Density Estimation for Informatively Censored Data
Abstract
Selection biases occur often in sampling and have wide application in almost all areas, such as economics, social sciences, and clinical trials. In survival data analysis, whether a data point is censored could depend on the true value of the data point. In this talk, we will discuss the informative censoring mechanism in the generalized Type I censoring. A non-parametric method will be proposed to estimate the density from data with informative censoring. A real data application will be demonstrated.
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