JSM 2004 - Toronto

Abstract #301118

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Activity Number: 190
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 8:30 AM to 10:20 AM
Sponsor: General Methodology
Abstract - #301118
Title: Exploring Intrinsic Dependence with CID
Author(s): Tailen Hsing and Li-yu D. Liu*+ and Marcel Brun and Edward R. Dougherty
Companies: Texas A&M University and Texas A&M University and Texas A&M University and Texas A&M University
Address: 3143 TAMU, College Station, TX, 77843-3143,
Keywords: dependence ; prediction ; classification
Abstract:

We introduce a new measure of dependence, the coefficient of intrinsic dependence or CID, between two sets of variables. CID is model-free, invariant under monotone transformations of the variables, and is capable of fully differentiate different degrees of dependence. The estimation of CID can be carried out nonparametrically based on the ranks of the data, and the MSE of the estimator can be seen to decrease quickly with sample size. The applications that we discuss include testing for dependence, variable selection, parameter estimation in generalized linear models, and genetics data analysis.

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