Deconvolution problems occur in many fields of nonparametric statistics, for example,
density estimation based on contaminated data, nonparametric regression with errors-in …

Supplement to “Multiscale scanning in inverse problems”. This supplementary material
contains an explanation of the full width at half maximum (FWHM), a detailed mathematical …

Multiscale methods for shape constraints in deconvolution: Confidence statements for qualitative
features Page 1 The Annals of Statistics 2013, Vol. 41, No. 3, 1299–1328 DOI …

In this paper, we consider ill-posed inverse problem models Y= Tf+ εξ where T denotes a
compact operator, ε a noise level, ξ a Gaussian white noise and f the function of interest …

We consider nonparametric estimation of the density of a variable which is observed with an
independent additive noise of known distribution. We introduce the classical measurement …

We consider a semiparametric convolution model. We observe random variables having a
distribution given by the convolution of some unknown density f and some partially known …

We consider spherical data X_i noised by a random rotation i∈SO(3) so that only the
sample Z_i=iX_i, i=1,\dots,N is observed. We define a nonparametric test procedure to …

In this paper we provide new methodology for inference of the geometric features of a
multivariate density in deconvolution. Our approach is based on multiscale tests to detect …

In a convolution model, we observe random variables whose distribution is the convolution
of some unknown density f and some known noise density g. We assume that g is …

We propose two test statistics for use in inverse regression problems Y= K θ+ ε, where K is a
given linear operator which cannot be continuously inverted. Thus, only noisy, indirect …