Deconvolution Problems in Nonparametric Statistics [electronic resource] /by Alexander Meister.
by Meister, Alexander [author.]; SpringerLink (Online service).
Material type:
BookSeries: Lecture Notes in Statistics: 193Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.Description: VI, 210p. online resource.ISBN: 9783540875574.Subject(s): Statistics | Mathematical statistics | Statistics | Statistical Theory and MethodsDDC classification: 519.5 Online resources: Click here to access online
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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.
Density Deconvolution -- Nonparametric Regression with Errors-in-Variables -- Image and Signal Reconstruction.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | QA276-280 (Browse shelf) | Available |
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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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