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Deconvolution Problems in Nonparametric Statistics [electronic resource] / by Alexander Meister.

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Statistics ; 193Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: VI, 210 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540875574
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519.2 23
LOC classification:
  • QA273.A1-274.9
  • QA274-274.9
Online resources:
Contents:
Density Deconvolution -- Nonparametric Regression with Errors-in-Variables -- Image and Signal Reconstruction.
In: Springer eBooksSummary: This book gives an introduction to deconvolution problems in nonparametric statistics, e.g. density estimation based on contaminated data, errors-in-variables regression, and image reconstruction. Some real-life applications are discussed while we mainly focus on methodology (description of the estimation procedures) and theory (minimax convergence rates with rigorous proofs and adaptive smoothing parameter selection). In general, we have tried to present the proofs in such manner that only a low level of previous knowledge is needed. An appendix chapter on further results of Fourier analysis is also provided.
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Density Deconvolution -- Nonparametric Regression with Errors-in-Variables -- Image and Signal Reconstruction.

This book gives an introduction to deconvolution problems in nonparametric statistics, e.g. density estimation based on contaminated data, errors-in-variables regression, and image reconstruction. Some real-life applications are discussed while we mainly focus on methodology (description of the estimation procedures) and theory (minimax convergence rates with rigorous proofs and adaptive smoothing parameter selection). In general, we have tried to present the proofs in such manner that only a low level of previous knowledge is needed. An appendix chapter on further results of Fourier analysis is also provided.

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