In this paper, we propose to construct confidence bands by bootstrapping the debiased
kernel density estimator (for density estimation) and the debiased local polynomial …

Testing of hypotheses is a well studied topic in mathematical statistics. Recently, this issue
has also been addressed in the context of inverse problems, where the quantity of interest is …

Errors-in-variables regression is important in many areas of science and social science, eg
in economics where it is often a feature of hedonic models, in environmental science where …

This paper develops a method to construct uniform confidence bands for a nonparametric
regression function where a predictor variable is subject to a measurement error. We allow …

Uniform asymptotic confidence bands for a multivariate regression function in an inverse
regression model with a convolution-type operator are constructed. The results are derived …

This paper is concerned with inference on the cumulative distribution function (cdf) FX∗ in
the classical measurement error model X= X∗+ ϵ. We consider the case where the density …

Recovering a function f from its integrals over hyperplanes (or line integrals in the two-
dimensional case), that is, recovering f from the Radon transform R f of f, is a basic problem …

We study a nonparametric Bayesian approach to linear inverse problems under discrete
observations. We use the discrete Fourier transform to convert our model into a truncated …

In this appendix we collect the mathematical elements, mainly from operator theory, that
serve as the underlying language and building blocks for this thesis. They are from well …

In a recent paper Birke and Bissantz (2009) considered the problem of nonparametric
estimation in inverse regression models with convolution-type operators. For multivariate …