On linearization of nonparametric deconvolution estimators for repeated measurements model

Daisuke Kurisu and Taisuke Otsu

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: By utilizing intermediate Gaussian approximations, this paper establishes asymptotic linear representations of nonparametric deconvolution estimators for the classical measurement error model with repeated measurements. Our result is applied to derive confidence bands for the density and distribution functions of the error-free variable of interest and to establish faster convergence rates of the estimators than the ones obtained in the existing literature. Due to slower decay rates of the linearization errors, however, our bootstrap counterparts for confidence bands need to be constructed by subsamples.

Keywords: asymptotic linear representation; confidence band; deconvolution; intermedia Gaussian approximation; measurement error (search for similar items in EconPapers)
JEL-codes: J1 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2022-05-01
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Published in Journal of Multivariate Analysis, 1, May, 2022, 189. ISSN: 0047-259X

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:112676

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