Abstract #301252

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JSM 2002 Abstract #301252
Activity Number: 183
Type: Contributed
Date/Time: Tuesday, August 13, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing*
Abstract - #301252
Title: On the Use of Independent Component Analysis to Separate Meaningful Sources in Global Temperature Series
Author(s): Imola Fodor*+ and Chandrika Kamath
Affiliation(s): Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory
Address: P.O. Box 808, L-560, Livermore, California, 94551,
Keywords: Statistical computing ; Independent component analysis ; Time series analysis ; Climate data
Abstract:

Global temperature series have contributions from different sources, such as volcanic eruptions and El Ni\~no/Southern Oscillation variations. We investigate independent component analysis (ICA) as a technique to separate unrelated sources present in such series. We first use artificial data, with known independent components, to study the conditions under which ICA separates the individual sources. We then illustrate the method with climate data from the National Centers for Environmental Prediction.

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