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ORTHONORMAL SERIES ESTIMATORS

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  • 304 stránek
  • 11 hodin čtení

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Focusing on advanced statistical methods, this book explores the approximation and estimation of nonparametric functions through projections onto orthonormal function bases. It introduces series estimators that enhance density estimators for various complex models, including mixture, deconvolution, and semi-parametric models. The authors demonstrate optimal convergence rates in Hilbert spaces and analyze mean square errors relative to basis size, utilizing cross-validation for consistent estimation. Additionally, wavelet estimators are examined within these frameworks, providing a comprehensive approach to modern data analysis techniques.

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ORTHONORMAL SERIES ESTIMATORS, Odile Pons

Jazyk
Rok vydání
2020
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Titul
ORTHONORMAL SERIES ESTIMATORS
Jazyk
anglicky
Autoři
Odile Pons
Rok vydání
2020
Vazba
pevná
Počet stran
304
ISBN13
9789811210686
Série
Anotace
Focusing on advanced statistical methods, this book explores the approximation and estimation of nonparametric functions through projections onto orthonormal function bases. It introduces series estimators that enhance density estimators for various complex models, including mixture, deconvolution, and semi-parametric models. The authors demonstrate optimal convergence rates in Hilbert spaces and analyze mean square errors relative to basis size, utilizing cross-validation for consistent estimation. Additionally, wavelet estimators are examined within these frameworks, providing a comprehensive approach to modern data analysis techniques.