Sensitivity and other properties of wavelet regression and density estimators

Statistica Sinica

Volumn 12, Issue 4, 2002, Pages 1275-1290

  Renaud, Olivier ^a  

^a UNIVERSITY OF GENEVA   (Switzerland)

Author keywords

Approximation kernel; Functional; Influence function; Irregular design; Sensitivity to the design; Shift invariance

Indexed keywords

EID: 0036822492     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

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2. Daubechies, I. (1988). Orthonormal bases of compactly supported wavelets. Comm. Pure Appl. Math. 41, 909-996.
3. Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J. and Stahel, W. A. (1986). Robust Statistics: The Approach Based on Influence Functions. Wiley, New York.
4. Kovac, A. and Silverman, B. W. (2000). Extending the scope of wavelet regression methods by coefficient-dependent thresholding. J. Amer. Statist. Assoc. 95, 172-183.
5. Renaud, O. (1999). Shift-invariant wavelet density estimator with smaller variability. Submitted.
6. Sardy, S. (1998). Regularization techniques for linear regression with a large set of carries. Ph. D. thesis, University of Washington.
7. Sardy, S., Percival, D., Bruce, A., Gao, H.-Y. and Stuetzle, W. (1999). Wavelet de-noising for unequally spaced data. Statist. Comput. 9, 65-75.
8. Vidakovic, B. (1999). Statistical Modeling by Wavelets. Wiley, New York.