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Deconvolution Problems in Nonparametric Statistics
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 esti...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2009.
|
| Edición: | 1st ed. 2009. |
| Colección: | Lecture Notes in Statistics,
193 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 245 | 1 | 0 | |a Deconvolution Problems in Nonparametric Statistics |h [electronic resource] / |c by Alexander Meister. |
| 250 | |a 1st ed. 2009. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2009. | |
| 300 | |a VI, 210 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Lecture Notes in Statistics, |x 2197-7186 ; |v 193 | |
| 505 | 0 | |a Density Deconvolution -- Nonparametric Regression with Errors-in-Variables -- Image and Signal Reconstruction. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Probabilities. | |
| 650 | 0 | |a Statistics . | |
| 650 | 1 | 4 | |a Probability Theory. |
| 650 | 2 | 4 | |a Statistical Theory and Methods. |
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| 830 | 0 | |a Lecture Notes in Statistics, |x 2197-7186 ; |v 193 | |
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