RAND Statistics Seminar Series

Data Large-Scale Prediction Problems

Presented by Professor Bradley Efron, Stanford University
Thursday, May 21, 2009
10:30 a.m. – 12:00 p.m. PT / 1:30pm – 3:00pm ET
Conference Room 1226 and 1228
RAND Corporation, Santa Monica, CA
Please contact Denise Miller if you would like to attend this seminar.

Abstract

Classical prediction methods such as Fisher's linear discriminant function were designed for small-scale problems, where the number N of candidate predictors was much smaller than the number of observations n. Modern scientific devices often reverse this situation. A microarray analysis, for example, might include n=100 subjects measured on N=10,000 genes, each of which is a potential predictor. I will discuss "Ebay", an empirical Bayes prediction algorithm designed to handle N >> n situations. It is closely related to the Shrunken Centroids algorithm of Tibshirani, Hastie, Narasimhan, and Chu.

Speaker Bio

Dr. Efron, the Max H. Stein Professor and Professor of Statistics and of Health Research and Policy, recently received the National Medal of Science and was cited "for his contributions to theoretical and applied statistics, especially the bootstrap sampling technique; for his extraordinary geometric insight into nonlinear statistical problems; and for applications in medicine, physics and astronomy." He previously had been awarded the Ford Prize, MacArthur Prize, and the Wilks Medal and has served as president of the American Statistical Association and of the Institute of Mathematical Statistics. Dr. Efron's work has spanned both theoretical and applied topics, including empirical Bayes analysis, applications of differential geometry to statistical inference, the analysis of survival data, and inference for microarray gene expression data.



Attending a Seminar

Other Locations/Times:
Washington, D.C. Conf. Rm. 4132: 1:30 p.m. ET
Pittsburgh Conf. Rm. 6202: 1:30 p.m. ET

RAND visitors are welcome to attend and must RSVP at least one day prior to the seminar. To ensure your attendance please contact Denise Miller at dmiller@rand.org with your name, company (or university) affiliation, and national citizenship (for security purposes).

For parking and directions to RAND's Santa Monica office, please see: http://www.rand.org/about/locations/santa-monica.html.

For parking and directions to RAND's Pittsburgh office, please see: http://www.rand.org/about/locations/pittsburgh.html.

For further information and to be added to the mailing list contact Denise Miller at dmiller@rand.org.