Asymptotic normality and confidence intervals for inverse regression models with convolution-type operators

DOI10.1016/j.jmva.2009.04.004zbMath1175.62035OpenAlexW1989659408MaRDI QIDQ1036801

Nicolai Bissantz, Melanie Birke

Publication date: 13 November 2009

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2003/25880

zbMATH Keywords

bootstrapmodel selectioninverse problemstesting

Mathematics Subject Classification ID

Related Items (8)

Model Checks in Inverse Regression Models with Convolution-Type Operators ⋮ A note on confidence intervals for deblurred images ⋮ Wavelet Estimation for Regression Convolution Model with Heteroscedastic Errors ⋮ Asymptotic confidence bands in the Spektor-Lord-Willis problem via kernel estimation of intensity derivative ⋮ Testing for symmetries in multivariate inverse problems ⋮ Additive inverse regression models with convolution-type operators ⋮ Nonparametric inference via bootstrapping the debiased estimator ⋮ Confidence bands for multivariate and time dependent inverse regression models

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