Partial heteroscedastic deconvolution estimation in nonparametric regression

Baba Thiam

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arXiv · 2601.20341

Partial heteroscedastic deconvolution estimation in nonparametric regression

Baba Thiam

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Abstract

In this paper, we consider a partial deconvolution kernel estimator for nonparametric regression when some covariates are measured with error while others are observed without error. We focus on a general and realistic setting in which the measurement errors are heteroscedastic. We propose a kernel-based estimator of the regression function in this framework and show that it achieves the optimal convergence rate under suitable regularity conditions. The finite-sample performance of the proposed estimator is illustrated through simulation studies.

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Baba Thiam. 2026-01-28. Partial heteroscedastic deconvolution estimation in nonparametric regression. https://arxiv.org/abs/2601.20341

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