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Abstract Details
Activity Number:
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156
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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International Chinese Statistical Association
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Abstract - #301018 |
Title:
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Spline Confidence Bands for Functional Derivatives
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Author(s):
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Guanqun Cao and Jing Wang*+ and Li Wang and David Todem
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Companies:
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Michigan State University and University of Illinois at Chicago and University of Georgia and Michigan State University
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Address:
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851 S Morgan St (MC 249), Chicago, IL, 60607,
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Keywords:
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B-spline ;
confidence band ;
functional data ;
derivative ;
semiparametric efficiency
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Abstract:
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This paper considers the problem of estimating the derivatives of the mean curve of dense functional data. In particular, confidence bands for the derivative curves are developed using polynomial B-splines. Both the spline estimator and its accompanying confidence band are shown to have the semiparametric efficiency in the sense that they are asymptotically the same as if all random trajectories are observed entirely and without errors. The confidence band procedure is illustrated through several numerical studies.
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