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Asymptotic normality of nonparametric kernel type deconvolution density estimators: crossing the Cauchy boundary
Authors:
A. J. van Es a;
H. -W. Uh b
| Affiliations: | a Korteweg-de Vries Institute for Mathematics, University of Amsterdam, TV Amsterdam, The Netherlands |
| b Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands |
DOI:
10.1080/10485250310001644574
Publication Frequency:
8 issues per year
Published in:
Journal of Nonparametric Statistics,
Volume
16,
Issue
1 &
2
February
2004
, pages 261
- 277
Journal of Nonparametric Statistics,
Volume
16,
Issue
1 &
2
February
2004
, pages 261
- 277
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Number of References: 13
Formats available:
PDF
(English)
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Abstract
We derive asymptotic normality of kernel type deconvolution density estimators. In particular, we consider deconvolution problems where the known component of the convolution has a symmetric λ-stable distribution with 0 < λ ≤ 2. It turns out that the limit behavior changes if the exponent parameter λ passes the value 1, the case of Cauchy deconvolution.
|
| Keywords: Deconvolution; Kernel estimation; Asymptotic normality |
| view references (13) |
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