Title
Density Deconvolution Of Different Conditional Distributions
Keywords
Deconvolution; Ill-posed problem; Probability density
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 case of uniform and triangular distributions.
Publication Date
12-1-2002
Publication Title
Annals of the Institute of Statistical Mathematics
Volume
54
Issue
3
Number of Pages
701-712
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1023/A:1022435832605
Copyright Status
Unknown
Socpus ID
12244304144 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/12244304144
STARS Citation
Pensky, Marianna and Zayed, Ahmed I., "Density Deconvolution Of Different Conditional Distributions" (2002). Scopus Export 2000s. 2311.
https://stars.library.ucf.edu/scopus2000/2311