Nickl richard (25 risultati)

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Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.ThriftBooks-Dallas
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EUR 31,92
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Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Lingua: Inglese
Editore: Cambridge University Press, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 61,50
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Condizione: New.

Lingua: Inglese
Editore: Cambridge University Press, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 65,03
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Condizione: As New. Unread book in perfect condition.

Lingua: Inglese
Editore: Cambridge University Press, GB, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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EUR 82,60
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Paperback. Condizione: New. In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a cohere…nt account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics.

Lingua: Inglese
Editore: Cambridge University Press, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 64,58
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Condizione: New.

Lingua: Inglese
Editore: Cambridge University Press, 2021
Serie: Libro 29 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 71,02
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Condizione: As New. Unread book in perfect condition.

Lingua: Inglese
Editore: Cambridge University Press, 2021
Serie: Libro 29 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 87,22
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been develope…d in the past several decades. This book gives a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 137,78
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Condizione: New.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: California Books, Miami, FL, U.S.A.California Books
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EUR 140,13
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Condizione: New.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 137,78
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Condizione: As New. Unread book in perfect condition.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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EUR 127,19
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Condizione: New. In.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 127,18
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Condizione: New.

Lingua: Inglese
Editore: Cambridge University Press, GB, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Brossura
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 80,54
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Paperback. Condizione: New. In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a cohere…nt account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 141,32
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Condizione: As New. Unread book in perfect condition.

Lingua: Inglese
Editore: Cambridge University Press, GB, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 174,52
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Hardback. Condizione: New. In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a coheren…t account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, on approximation and wavelet theory, and on the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is then presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In the final chapter, the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions.

Lingua: Inglese
Editore: Cambridge University Press CUP, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 179,31
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Condizione: New. pp. 720.

Lingua: Inglese
Editore: Cambridge Univ Pr, 2016
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 181,86
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Hardcover. Condizione: Brand New. 1st edition. 720 pages. 10.37x7.04x1.71 inches. In Stock.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 29 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 171,32
EUR 41,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in th…e past several decades. This book gives a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, on approximation and wavelet theory, and on the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is then presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In the final chapter, the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions.

Lingua: Inglese
Editore: Cambridge University Press, GB, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 170,51
EUR 75,65 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Hardback. Condizione: New. In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a coheren…t account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, on approximation and wavelet theory, and on the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is then presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In the final chapter, the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions.

Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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Paperback. Condizione: new. Paperback. In nonparametric and high-dimensional statistical models, the classical GaussFisherLe Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives… a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics. High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples or from Gaussian regression/signal in white noise problems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Lingua: Inglese
Editore: Cambridge University Press, 2021
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 66,56
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus o…n function estimation problems arising fr.

Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 136,64
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Hardcover. Condizione: new. Hardcover. In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book giv…es a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, on approximation and wavelet theory, and on the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is then presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In the final chapter, the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples (density estimation) or from Gaussian regression/signal in white noise problems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Lingua: Inglese
Editore: Cambridge University Press, 2017
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 131,84
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus o…n function estimation problems arising fr.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 185,32
EUR 7,56 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand pp. 720.

Lingua: Inglese
Editore: Cambridge University Press, 2015
Serie: Libro 44 di 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 189,48
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND pp. 720.