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This article is cited in 11 scientific papers (total in 11 papers)
Asymptotic efficiency of inverse estimators
A. C. M. Van Rooija, F. H. Ruymgaartb, W. R. Van Zwetc a Katholieke Universiteit Nijmegen
b Texas Tech University, Department of Mathematics
c Rijksuniversiteit Leiden
Abstract:
Inverse estimation concerns the recovery of an unknown input signal from blurred observations on a known transformation of that signal. The estimators considered in this paper are based on a regularized inverse of the transformation involved, employing a Hilbert space set-up. We focus on properties related to weak convergence. It is shown that linear functionals can be efficiently estimated in the Hájek–LeCam sense, provided they remain restricted to a suitable class. Outside this class, rates different from $\sqrt{n}$ are possible. By way of an example we present the ‘`convolution theorem’ for a deconvolution.
Keywords:
inverse estimation, weak convergence, asymptotic efficiency, Hájek–LeCam convolution theorem.
Received: 12.11.1997 Revised: 28.04.1998
Citation:
A. C. M. Van Rooij, F. H. Ruymgaart, W. R. Van Zwet, “Asymptotic efficiency of inverse estimators”, Teor. Veroyatnost. i Primenen., 44:4 (1999), 826–844; Theory Probab. Appl., 44:4 (2000), 722–738
Linking options:
https://www.mathnet.ru/eng/tvp1067https://doi.org/10.4213/tvp1067 https://www.mathnet.ru/eng/tvp/v44/i4/p826
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