Deconvolution Problems in Nonparametric Statistics

  • Alexander Meister

Part of the Lecture Notes in Statistics book series (LNS, volume 193)

Also part of the Lecture Notes in Statistics - Proceedings book sub series (volume 193)

Table of contents

  1. Front Matter
    Pages i-vi
  2. Alexander Meister
    Pages 1-3
  3. Alexander Meister
    Pages 5-105
  4. Alexander Meister
    Pages 107-149
  5. Alexander Meister
    Pages 151-177
  6. Back Matter
    Pages 179-210

About this book

Introduction

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.

Keywords

Contaminated data Deconvolution Density Estimation Fourier Analysis Image Reconstruction Parametric statistics calculus statistics

Authors and affiliations

  • Alexander Meister
    • 1
  1. 1.Fak. Mathematik undUniversität UlmUlmGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-87557-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-540-87556-7
  • Online ISBN 978-3-540-87557-4
  • Series Print ISSN 0930-0325
  • About this book