Variable Selection with The Modified Buckley–James Method
March 30, 2013 – 6:05pm
Full Title:
Variable Selection with The Modified Buckley–James Method and The Dantzig Selector for High–dimensional Survival Data
Speaker:
Hasinur Rahaman Khan, MSc
University of Dhaka, Bangladesh
Date/Time:
Saturday, April 13, 2013, 3:30pm
Venue:
ISRT Seminar Room
ABSTRACT
We consider variable selection techniques for high-dimensional survival data. We develop five algorithms for variable selection suitable for right censored data. The approaches can be used for parameter estimation and prediction for survival time with both low and high–dimensional data. The first two algorithms are based on a synthesis of the Buckley–James methods and the Dantzig Selector. The remaining algorithms are based on the weighted Dantzig selector where weights are obtained using the synthesis based algorithms. The algorithms are simple and scalable. The algorithms can deal with collinearity among the covariates and also among the groups of the covariates. We conduct several simulation studies and one empirical analysis with a microarray dataset. The proposed algorithms work very well for selecting sparse model or smaller variable subsets under many practical conditions.
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Mailing Address
Director,
Institute of Statistical Research and Training (ISRT)
University of Dhaka
Dhaka 1000, Bangladesh