Nickl richard (23 risultati)
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Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.ThriftBooks-Dallas
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Buono
EUR 8,97
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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: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 62,29
EUR 2,30 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Lingua: Inglese
Editore: Cambridge University Press 2021
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 65,60
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Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Cambridge University Press 2021
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 63,93
EUR 17,28 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Lingua: Inglese
Editore: Cambridge University Press 2021
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - 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 70,36
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Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Cambridge University Press 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 133,04
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Condizione: New.
Lingua: Inglese
Editore: Cambridge University Press 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - 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 119,85
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Condizione: New. In.
Lingua: Inglese
Editore: Cambridge University Press 2021
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 84,40
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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, GB 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 173,29
Spedizione gratuitaSpedito 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 CUP 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - 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 181,75
EUR 3,48 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New. pp. 720.
Lingua: Inglese
Editore: Cambridge Univ Pr 2016
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 183,65
EUR 17,28 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Hardcover. Condizione: Brand New. 1st edition. 720 pages. 10.37x7.04x1.71 inches. In Stock.
Lingua: Inglese
Editore: Cambridge University Press, GB 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - 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 162,79
EUR 74,89 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 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 165,79
EUR 67,50 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.
Editore: Cambridge University Press
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Da: Academic Book Solutions, Medford, NY, U.S.A.Academic Book Solutions
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Discreto
EUR 116,96
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hardcover. Condizione: Acceptable. Damaged Binding, Pages still bound together., A readable copy. All pages are intact, and the cover is intact (the dust cover may be missing). Pages can include notes--in pen or highlighter.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge 2021
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 64,67
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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 multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge 2021
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 70,00
EUR 42,63 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
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: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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- Print on Demand
Da: moluna, Greven, , Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 66,56
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, Cambridge 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 133,03
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
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 multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Cambridge Univ Pr 2016
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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- Print on Demand
Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 123,88
EUR 17,28 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: Brand New. 1st edition. 720 pages. 10.37x7.04x1.71 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge 2015
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 135,27
EUR 42,63 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
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: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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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: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - 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 183,57
EUR 7,49 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: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 29 di 46. Libro 29 di 46 - 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 184,42
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND pp. 720.
