Deconvolution Problems in Nonparametric Statistics
Par :Formats :
- Nombre de pages210
- PrésentationBroché
- FormatGrand Format
- Poids0.334 kg
- Dimensions15,5 cm × 23,5 cm × 1,1 cm
- ISBN978-3-540-87556-7
- EAN9783540875567
- Date de parution01/03/2009
- CollectionLecture Notes in Statistics
- ÉditeurSpringer
Résumé
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 (minima 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.
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.
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 (minima 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.
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.