JSM 2005 Online Program

Abstract #304505

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	359
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor:	General Methodology
Abstract - #304505
Title:	Regularized Discriminant Analysis and Its Application in Microarrays
Author(s):	Yaqian Guo*+ and Trevor Hastie and Robert Tibshirani
Companies:	Stanford University and Stanford University and Stanford University
Address:	126 Blackwelder Court, Stanford, CA, 94305, United States
Keywords:	Classification ; Discriminant analysis ; Microarray ; Prediction analysis of microarrays ; Regularization ; Shrunken centriods
Abstract:	We introduce a modified version of linear discriminant analysis called shrunken centroids regularized discriminant analysis (SCRDA). This method generalizes the idea of the nearest shrunken centroids (NSC) method into the classical discriminant analysis.The SCRDA method is specially designed for classification problems in high-dimension, low sample size situations such as microarray data. Through both simulated data and real-life data, it is shown that it performs well in multivariate classification problems, often outperforms the PAM method, and can be as competitive as some support vector machine (SVM) classifiers. It also is suitable for feature elimination purpose and can be used as gene selection method. The open source R package for SCRDA is also available.

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