JSM 2004 - Toronto

Abstract #300275

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Activity Number: 322
Type: Invited
Date/Time: Wednesday, August 11, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #300275
Title: Lasso Methods for Computational Biology
Author(s): Rob Tibshirani*+
Companies: Stanford University
Address: HRP Redwood Bldg., Room T101C, Stanford, CA, 94305-5405,
Keywords:
Abstract:

The Lasso is a shrinkage and selection method for linear regression. It minimizes the usual sum of squared errors, with a bound on the sum of the absolute values of the coefficients. It has connections to soft-thresholding of wavelet coefficients, forward stagewise regression, and boosting methods. We illustrate how this set of techniques can be applied to analyse microarray data and, more generally, to solve computational biology problems.

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Revised March 2004