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Abstract Details
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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 - #301317 |
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Title:
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On Equivalent Kernels for (Periodic) Spline Estimators
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Author(s):
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Tatyana Krivobokova*+ and Katja Schwarz
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Companies:
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Georg-August-Universitaet Goettingen and Georg-August-Universitaet Goettingen
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Address:
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, Goettingen, 37073, Germany
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Keywords:
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Penalized splines ;
Equivalent kernels
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Abstract:
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In this work we study general spline based estimators, where both the number of knots and the smoothing parameter control the (asymptotic) properties of estimators. This includes both extreme cases: least squares (regression) spline estimators (with smoothing parameter equal to zero) and smoothing spline estimators (with the number of knots equal to the number of observations). Applying Fourier techniques we study in a unified framework the asymptotic properties of spline based estimators. We discuss two asymptotic scenarios possible, depending on the number of knots chosen. In particular, we obtain the equivalent and reproducing kernel as a function of number of knots and smoothing parameter and present some results on the local asymptotics for these general spline estimators.
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