Authors: Eckle, Konstantin
Bissantz, Nicolai
Dette, Holger
Title: Multiscale inference for multivariate deconvolution
Language (ISO): en
Abstract: We propose multiscale tests for deconvolution in order to detect geometric features of an unknown multivariate density. Our approach uses simultaneous tests on all scales for the monotonicity of the density at arbitrary points in arbitrary directions. We consider the situation of polynomial decay of the Fourier transform of the error density in the de- convolution model (moderately ill-posed). We develop multiscale methods for identifying regions of monotonicity and a general procedure to detect the modes of a multivariate density. The theoretical results are illustrated by means of a simulation study.
Subject Headings: multiple tests
X-ray astronomy
multivariate density
modes
URI: http://hdl.handle.net/2003/35310
http://dx.doi.org/10.17877/DE290R-17353
Issue Date: 2016
Appears in Collections:Sonderforschungsbereich (SFB) 823

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