JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 335
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #306619
Title: Dependence Measures for Functional Observations
Author(s): Juan Romo*+ and Rosa E. Lillo and Dalia Valencia
Companies: Universidad Carlos III de Madrid and Universidad Carlos III de Madrid and Universidad Carlos III de Madrid
Address: Madrid, 126, 28903 Getafe, Madrid, _, , Spain
Keywords: Functional data ; Kendall's coefficient

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.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.