Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics)

0 durchschnittliche Bewertung
( 0 Bewertungen bei Goodreads )
 
9781107043169: Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics)
Alle Exemplare der Ausgabe mit dieser ISBN anzeigen:
 
 

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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Críticas:

'Finally - a book that goes all the way in the mathematics of nonparametric statistics. It is reasonably self-contained, despite its depth and breadth, including accessible overviews of the necessary analysis and approximation theory.' Aad van der Vaart, Universiteit Leiden

'This remarkable book provides a detailed account of a great wealth of mathematical ideas and tools that are crucial in modern statistical inference, including Gaussian and empirical processes (where the first author, Evarist Giné, was one of the key contributors), concentration inequalities and methods of approximation theory. Building upon these ideas, the authors develop and discuss a broad spectrum of statistical applications such as minimax lower bounds and adaptive inference, nonparametric likelihood methods and Bayesian nonparametrics. The book will be exceptionally useful for a great number of researchers interested in nonparametric problems in statistics and machine learning, including graduate students.' Vladimir Koltchinskii, Georgia Institute of Technology

'This is a very welcome contribution. The wealth of material on the empirical processes and nonparametric statistics is quite exceptional. It is a masterly written treatise offering an unprecedented coverage of the classical theory of nonparametric inference, with glimpses into advanced research topics. For the first time in the monographic literature, estimation, testing and confidence sets are treated in a unified way from the nonparametric perspective with a comprehensive insight into adaptation issues. A delightful major reading that I warmly recommend to anyone wanting to explore the mathematical foundations of these fields.' Alexandre Tsybakov, ENSAE ParisTech

'This is a remarkably comprehensive, detailed and rigorous treatment of mathematical theory for non-parametric and high-dimensional statistics. Special emphasis is on density and regression estimation and corresponding confidence sets and hypothesis testing. The minimax paradigm and adaptivity play a key role.' Natalie Neumeyer, MathSciNet

Reseña del editor:

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 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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Beste Suchergebnisse bei AbeBooks

1.

Gine, Evarist
Verlag: Cambridge University Press (2015)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Anzahl: > 20
Print-on-Demand
Anbieter
Pbshop
(Wood Dale, IL, USA)
Bewertung
[?]

Buchbeschreibung Cambridge University Press, 2015. HRD. Zustand: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers IQ-9781107043169

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 74,58
Währung umrechnen

In den Warenkorb

Versand: EUR 3,41
Innerhalb USA
Versandziele, Kosten & Dauer

2.

Gin?, Evarist
Verlag: Cambridge University Press
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Anzahl: 1
Anbieter
TextbookRush
(Grandview Heights, OH, USA)
Bewertung
[?]

Buchbeschreibung Cambridge University Press. Zustand: Brand New. Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy. Bestandsnummer des Verkäufers 43403999

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 75,76
Währung umrechnen

In den Warenkorb

Versand: EUR 3,41
Innerhalb USA
Versandziele, Kosten & Dauer

3.

Gine, Evarist
Verlag: Cambridge University Press (2015)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Anzahl: > 20
Print-on-Demand
Anbieter
Books2Anywhere
(Fairford, GLOS, Vereinigtes Königreich)
Bewertung
[?]

Buchbeschreibung Cambridge University Press, 2015. HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers IQ-9781107043169

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 75,10
Währung umrechnen

In den Warenkorb

Versand: EUR 10,17
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

4.

Giné, Evarist
Verlag: Cambridge University Press (2018)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: 18
Print-on-Demand
Anbieter
Murray Media
(North Miami Beach, FL, USA)
Bewertung
[?]

Buchbeschreibung Cambridge University Press, 2018. Hardcover. Zustand: New. Never used! This item is printed on demand. Bestandsnummer des Verkäufers 1107043166

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 97,35
Währung umrechnen

In den Warenkorb

Versand: Gratis
Innerhalb USA
Versandziele, Kosten & Dauer

5.

Giné, Evarist/ Nickl, Richard
Verlag: Cambridge Univ Pr (2016)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: 1
Anbieter
Revaluation Books
(Exeter, Vereinigtes Königreich)
Bewertung
[?]

Buchbeschreibung Cambridge Univ Pr, 2016. Hardcover. Zustand: Brand New. 1st edition. 720 pages. 10.37x7.04x1.71 inches. In Stock. Bestandsnummer des Verkäufers __1107043166

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 94,64
Währung umrechnen

In den Warenkorb

Versand: EUR 8,48
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

6.

Evarist Giné, Richard Nickl
Verlag: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2015)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: 10
Print-on-Demand
Anbieter
Book Depository International
(London, Vereinigtes Königreich)
Bewertung
[?]

Buchbeschreibung CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2015. Hardback. Zustand: New. Language: English . Brand New Book ***** Print on Demand *****. 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 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. Bestandsnummer des Verkäufers APC9781107043169

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 104,50
Währung umrechnen

In den Warenkorb

Versand: Gratis
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

7.

Evarist Giné, Richard Nickl
Verlag: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2015)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: 10
Print-on-Demand
Anbieter
The Book Depository
(London, Vereinigtes Königreich)
Bewertung
[?]

Buchbeschreibung CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2015. Hardback. Zustand: New. Language: English . Brand New Book ***** Print on Demand *****.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 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. Bestandsnummer des Verkäufers APC9781107043169

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 104,54
Währung umrechnen

In den Warenkorb

Versand: Gratis
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

8.

EVARIST GINÉ , RICHARD NICKL
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: 1
Anbieter
Herb Tandree Philosophy Books
(Stroud, GLOS, Vereinigtes Königreich)
Bewertung
[?]

Buchbeschreibung 2016. Hardback. Zustand: NEW. 9781107043169 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. For all enquiries, please contact Herb Tandree Philosophy Books directly - customer service is our primary goal. Bestandsnummer des Verkäufers HTANDREE01006628

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 95,92
Währung umrechnen

In den Warenkorb

Versand: EUR 9,02
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

9.

Giné, Evarist/ Nickl, Richard
Verlag: Cambridge Univ Pr (2016)
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: 2
Anbieter
Revaluation Books
(Exeter, Vereinigtes Königreich)
Bewertung
[?]

Buchbeschreibung Cambridge Univ Pr, 2016. Hardcover. Zustand: Brand New. 1st edition. 720 pages. 10.37x7.04x1.71 inches. In Stock. Bestandsnummer des Verkäufers x-1107043166

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 104,18
Währung umrechnen

In den Warenkorb

Versand: EUR 8,48
Von Vereinigtes Königreich nach USA
Versandziele, Kosten & Dauer

10.

Evarist Gin
Verlag: Cambridge University Press
ISBN 10: 1107043166 ISBN 13: 9781107043169
Neu Hardcover Anzahl: > 20
Anbieter
BuySomeBooks
(Las Vegas, NV, USA)
Bewertung
[?]

Buchbeschreibung Cambridge University Press. Hardcover. Zustand: New. 720 pages. 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 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 a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepskis method, wavelet thresholding, and adaptive inference for self-similar functions. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Hardcover. Bestandsnummer des Verkäufers 9781107043169

Weitere Informationen zu diesem Verkäufer | Verkäufer kontaktieren

Neu kaufen
EUR 116,96
Währung umrechnen

In den Warenkorb

Versand: Gratis
Innerhalb USA
Versandziele, Kosten & Dauer

Es gibt weitere Exemplare dieses Buches

Alle Suchergebnisse ansehen