Abstract Details
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Activity Number:
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484
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #308171 |
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Title:
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The Spatial Approach to Functional Data Analysis: Quantiles with Confidence Bands
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Author(s):
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Uditha Wijesuriya*+ and Robert Serfling
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Companies:
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The University of Texas at Dallas and The University of Texas at Dallas
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Keywords:
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Functional Data Analysis ;
Spatial Quantiles ;
Confidence Bands
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Abstract:
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The spatial or "geometric" approach toward multivariate quantiles has been very successful. Here its extension to functional data is treated. For a data set of real-valued curves, methods are described for useful display of the median curve, the 50% central region of curves, and the quantile curves for any selected ranks. The favorable computational aspects and convenient asymptotic normality of the sample spatial quantiles are discussed. It is shown how to apply the asymptotic normality to construct confidence bands for any population quantile. These techniques are illustrated with several data sets. A comparison is made with the fboxplot function in the Rainbow package in R, and it is seen that the spatial approach is more effective in identifying outliers.
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Authors who are presenting talks have a * after their name.
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