A Kendall correlation coefficient between functional data |
| |
Authors: | Valencia Dalia Lillo Rosa E Romo Juan |
| |
Institution: | 1.Department of Statistics, Universidad Carlos III de Madrid, Calle Madrid 126, Madrid, Spain ;2.Department of Statistics, UC3M-Santander Big Data Institute, Universidad Carlos III de Madrid, Madrid, Spain ; |
| |
Abstract: | Measuring dependence is a very important tool to analyze pairs of functional data. The coefficients currently available to quantify association between two sets of curves show a non robust behavior under the presence of outliers. We propose a new robust numerical measure of association for bivariate functional data. We extend in this paper Kendall coefficient for finite dimensional observations to the functional setting. We also study its statistical properties. An extensive simulation study shows the good behavior of this new measure for different types of functional data. Moreover, we apply it to establish association for real data, including microarrays time series in genetics.
|
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|