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Data-based optimal smoothing of a wavelet density estimator

✍ Scribed by H. Luo; J.E. Angus


Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
887 KB
Volume
26
Category
Article
ISSN
0895-7177

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✦ Synopsis


The problem of estimating a probability density function based on a complete random sample using a wavelet-based orthogonal expansion ie considered. We introduce linear modifications to the empirical wavelet expansion coefficients to control the smoothness of the estimator. A method for estimating the optimal smoothing coefficients from the data ia introduced. Finally, we prove that the estimator can achieve the optimal rate of convergence under mean integrated squared error as the sample size tends to infinity.

Keywords+ptimal

smoothing, Sobolev 8nd Hilbert space, Over-fitting, Under-fitting.


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