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Abstract Details
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Activity Number:
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335
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #306619 |
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Title:
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Dependence Measures for Functional Observations
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Author(s):
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Juan Romo*+ and Rosa E. Lillo and Dalia Valencia
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Companies:
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Universidad Carlos III de Madrid and Universidad Carlos III de Madrid and Universidad Carlos III de Madrid
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Address:
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Madrid, 126, 28903 Getafe, Madrid, _, , Spain
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Keywords:
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Functional data ;
Kendall's coefficient
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Abstract:
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Measuring dependence is a basic question when dealing with functional observations. Kendall's coefficient is a natural description of dependence between random variables. We extend this concept to functional data. Given a bivariate sample of functions, a robust analysis of dependence can be carried out through the functional version of Kendall correlation coefficient introduced in this talk. We also study its statistical properties and provide several applications to both simulated and real data, including asset portfolios in finance.
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