Title

Density deconvolution of different conditional distributions

Authors

Authors

M. Pensky;A. I. Zayed

Comments

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Abbreviated Journal Title

Ann. Inst. Stat. Math.

Keywords

deconvolution; ill-posed problem; probability density; ESTIMATING MIXING DENSITIES; NONPARAMETRIC DECONVOLUTION; MULTIVARIATE; DENSITIES; ASYMPTOTIC NORMALITY; STATIONARY-PROCESSES; INVERSE PROBLEMS; OPTIMAL RATES; WAVELET; DECOMPOSITION; CONVERGENCE; Statistics & Probability

Abstract

Recently, a new technique to circumvent the ill-posedness of the deconvolution problem has been suggested. This technique is based on what is known as multi-channel convolution system. In this paper, we modify and develop this technique in order to adapt it for statistical use. We then apply it to the problem of estimation of deconvolution density in the case of different conditional densities. This method enables us to combine equations efficiently for any set of conditional densities and to construct estimators in cases where the characteristic functions of the conditional distributions vanish at some points, as it happens in the cast of uniform and triangular distributions.

Journal Title

Annals of the Institute of Statistical Mathematics

Volume

54

Issue/Number

3

Publication Date

1-1-2002

Document Type

Article

Language

English

First Page

701

Last Page

712

WOS Identifier

WOS:000178679100019

ISSN

0020-3157

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