Title

Density deconvolution based on wavelets with bounded supports

Authors

Authors

M. Pensky

Comments

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Abbreviated Journal Title

Stat. Probab. Lett.

Keywords

deconvolution; wavelet; thresholding; NONPARAMETRIC DECONVOLUTION; INVERSE PROBLEMS; OPTIMAL RATES; DECOMPOSITION; CONVERGENCE; Statistics & Probability

Abstract

Under the assumption that both convolution densities, g and q, have finite degrees of smoothness, we construct a nonlinear wavelet estimator of the unknown density g based on wavelets with bounded supports. We show that this estimator provides local adaptivity to the unknown smoothness of g and, hence, performs better than the estimator based on Meyer-type wavelets if g has irregular behavior. (C) 2002 Elsevier Science B.V. All rights reserved.

Journal Title

Statistics & Probability Letters

Volume

56

Issue/Number

3

Publication Date

1-1-2002

Document Type

Article

DOI Link

http://dx.doi.org/10.1016/s0167-7152(01)00176-6

Language

English

First Page

261

Last Page

269

WOS Identifier

WOS:000174700500004

ISSN

0167-7152

Recommended Citation

"Density deconvolution based on wavelets with bounded supports" (2002). Faculty Bibliography 2000s. 3396.
https://stars.library.ucf.edu/facultybib2000/3396