Title

Adaptive Wavelet Estimator For Nonparametric Density Deconvolution

Keywords

Meyer wavelet; Mixing distribution; Sobolev space; Wavelet transformation

Abstract

The problem of estimating a density g based on a sample X1, X2, . . . , Xn from p = q * g is considered. Linear and nonlinear wavelet estimators based on Meyer-type wavelets are constructed. The estimators are asymptotically optimal and adaptive if g belongs to the Sobolev space Hα. Moreover, the estimators considered in this paper adjust automatically to the situation when g is supersmooth.

Publication Date

12-1-1999

Publication Title

Annals of Statistics

Volume

27

Issue

6

Number of Pages

2033-2053

Document Type

Article

Personal Identifier

scopus

Socpus ID

0033234633 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0033234633

This document is currently not available here.

Share

COinS