TSYBAKOV, ALEXANDRE B (52 Ergebnisse)

Paperback. Zustand: new. Paperback. La theorie de l'estimation non-parametrique s'est developpee considerablement ces deux dernieres decennies, en se fixant pour objectif quelques themes principaux, en particulier, l'etude de l'optimalite des estimateurs et l'estimation adaptative. Ces deux themes occupent la place centrale dans le livre. Il s'agit de presenter, pour quelques modeles et exemples simples, les idees principales de l'estimation non-parametrique. Quelques sujets abordes sont: les methodes de noyaux, de projection et de polynomes locaux, vitesses optimales de convergence, le theoreme de Pinsker, les inegalites d'oracle, l'adaptation au sens minimax. Un chapitre est consacre a l'exposition detaillee des differentes techniques de minoration du risque minimax. La theorie de l'estimation non-parametrique s'est developpee considerablement ces deux dernieres decennies, en se fixant pour objectif quelques themes principaux, en particulier, l'etude de l'optimalite des estimateurs et l'estimation adaptative. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Zustand: new. Paperback. This is a revised and extended version of the French book. The main changes are in Chapter 1 where the former Section 1. 3 is removed and the rest of the material is substantially revised. Sections 1. 2. 4, 1. 3, 1. 9, and 2. 7. 3 are new. Each chapter now has the bibliographic notes and contains the exercises section. I would like to thank Cristina Butucea, Alexander Goldenshluger, Stephan Huckenmann, Yuri Ingster, Iain Johnstone, Vladimir Koltchinskii, Alexander Korostelev, Oleg Lepski, Karim Lounici, Axel Munk, Boaz Nadler, AlexanderNazin,PhilippeRigollet,AngelikaRohde,andJonWellnerfortheir valuable remarks that helped to improve the text. I am grateful to Centre de Recherche en Economie et Statistique (CREST) and to Isaac Newton Ins- tute for Mathematical Sciences which provided an excellent environment for ?nishing the work on the book. My thanks also go to Vladimir Zaiats for his highly competent translation of the French original into English and to John Kimmel for being a very supportive and patient editor. Alexandre Tsybakov Paris, June 2008 Preface to the French Edition The tradition of considering the problem of statistical estimation as that of estimation of a ?nite number of parameters goes back to Fisher.However, parametric models provide only an approximation, often imprecise, of the - derlying statistical structure. Statistical models that explain the data in a more consistent way are often more complex: Unknown elements in these models are, in general, some functions having certain properties of smoo- ness. Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Zustand: New. pp. 228.

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Hardcover. Zustand: new. Hardcover. This is a revised and extended version of the French book. The main changes are in Chapter 1 where the former Section 1. 3 is removed and the rest of the material is substantially revised. Sections 1. 2. 4, 1. 3, 1. 9, and 2. 7. 3 are new. Each chapter now has the bibliographic notes and contains the exercises section. I would like to thank Cristina Butucea, Alexander Goldenshluger, Stephan Huckenmann, Yuri Ingster, Iain Johnstone, Vladimir Koltchinskii, Alexander Korostelev, Oleg Lepski, Karim Lounici, Axel Munk, Boaz Nadler, AlexanderNazin,PhilippeRigollet,AngelikaRohde,andJonWellnerfortheir valuable remarks that helped to improve the text. I am grateful to Centre de Recherche en Economie et Statistique (CREST) and to Isaac Newton Ins- tute for Mathematical Sciences which provided an excellent environment for ?nishing the work on the book. My thanks also go to Vladimir Zaiats for his highly competent translation of the French original into English and to John Kimmel for being a very supportive and patient editor. Alexandre Tsybakov Paris, June 2008 Preface to the French Edition The tradition of considering the problem of statistical estimation as that of estimation of a ?nite number of parameters goes back to Fisher.However, parametric models provide only an approximation, often imprecise, of the - derlying statistical structure. Statistical models that explain the data in a more consistent way are often more complex: Unknown elements in these models are, in general, some functions having certain properties of smoo- ness. Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Zustand: Neu. Neu Neuware, auf Lager - Methods of nonparametric estimation are located at the core of modern statistical science. The aim of this book is to give a short but mathematically self-contained introduction to the theory of nonparametric estimation. The emphasis is on the construction of optimal estimators; therefore the concepts of minimax optimality and adaptivity, as well as the oracle approach, occupy the central place in the book.This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results are not always given in the most general form but rather under assumptions that lead to shorter or more elegant proofs.The book has three chapters. Chapter 1 presents basic nonparametric regression and density estimators and analyzes their properties. Chapter 2 is devoted to a detailed treatment of minimax lower bounds. Chapter 3 develops more advanced topics: Pinsker's theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.

Taschenbuch. Zustand: Neu. Neuware -This is a revised and extended version of the French book. The main changes are in Chapter 1 where the former Section 1. 3 is removed and the rest of the material is substantially revised. Sections 1. 2. 4, 1. 3, 1. 9, and 2. 7. 3 are new. Each chapter now has the bibliographic notes and contains the exercises section. I would like to thank Cristina Butucea, Alexander Goldenshluger, Stephan Huckenmann, Yuri Ingster, Iain Johnstone, Vladimir Koltchinskii, Alexander Korostelev, Oleg Lepski, Karim Lounici, Axel Munk, Boaz Nadler, AlexanderNazin,PhilippeRigollet,AngelikaRohde,andJonWellnerfortheir valuable remarks that helped to improve the text. I am grateful to Centre de Recherche en Economie et Statistique (CREST) and to Isaac Newton Ins- tute for Mathematical Sciences which provided an excellent environment for nishing the work on the book. My thanks also go to Vladimir Zaiats for his highly competent translation of the French original into English and to John Kimmel for being a very supportive and patient editor. Alexandre Tsybakov Paris, June 2008 Preface to the French Edition The tradition of considering the problem of statistical estimation as that of estimation of a nite number of parameters goes back to Fisher. However, parametric models provide only an approximation, often imprecise, of the - derlying statistical structure. Statistical models that explain the data in a more consistent way are often more complex: Unknown elements in these models are, in general, some functions having certain properties of smoo- ness.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Methods of nonparametric estimation are located at the core of modern statistical science. The aim of this book is to give a short but mathematically self-contained introduction to the theory of nonparametric estimation. The emphasis is on the construction of optimal estimators; therefore the concepts of minimax optimality and adaptivity, as well as the oracle approach, occupy the central place in the book.This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results are not always given in the most general form but rather under assumptions that lead to shorter or more elegant proofs.The book has three chapters. Chapter 1 presents basic nonparametric regression and density estimators and analyzes their properties. Chapter 2 is devoted to a detailed treatment of minimax lower bounds. Chapter 3 develops more advanced topics: Pinsker's theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.

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Buch. Zustand: Neu. Neuware -This is a revised and extended version of the French book. The main changes are in Chapter 1 where the former Section 1. 3 is removed and the rest of the material is substantially revised. Sections 1. 2. 4, 1. 3, 1. 9, and 2. 7. 3 are new. Each chapter now has the bibliographic notes and contains the exercises section. I would like to thank Cristina Butucea, Alexander Goldenshluger, Stephan Huckenmann, Yuri Ingster, Iain Johnstone, Vladimir Koltchinskii, Alexander Korostelev, Oleg Lepski, Karim Lounici, Axel Munk, Boaz Nadler, AlexanderNazin,PhilippeRigollet,AngelikaRohde,andJonWellnerfortheir valuable remarks that helped to improve the text. I am grateful to Centre de Recherche en Economie et Statistique (CREST) and to Isaac Newton Ins- tute for Mathematical Sciences which provided an excellent environment for nishing the work on the book. My thanks also go to Vladimir Zaiats for his highly competent translation of the French original into English and to John Kimmel for being a very supportive and patient editor. Alexandre Tsybakov Paris, June 2008 Preface to the French Edition The tradition of considering the problem of statistical estimation as that of estimation of a nite number of parameters goes back to Fisher. However, parametric models provide only an approximation, often imprecise, of the - derlying statistical structure. Statistical models that explain the data in a more consistent way are often more complex: Unknown elements in these models are, in general, some functions having certain properties of smoo- ness.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch.

Paperback. Zustand: new. Paperback. This is a revised and extended version of the French book. The main changes are in Chapter 1 where the former Section 1. 3 is removed and the rest of the material is substantially revised. Sections 1. 2. 4, 1. 3, 1. 9, and 2. 7. 3 are new. Each chapter now has the bibliographic notes and contains the exercises section. I would like to thank Cristina Butucea, Alexander Goldenshluger, Stephan Huckenmann, Yuri Ingster, Iain Johnstone, Vladimir Koltchinskii, Alexander Korostelev, Oleg Lepski, Karim Lounici, Axel Munk, Boaz Nadler, AlexanderNazin,PhilippeRigollet,AngelikaRohde,andJonWellnerfortheir valuable remarks that helped to improve the text. I am grateful to Centre de Recherche en Economie et Statistique (CREST) and to Isaac Newton Ins- tute for Mathematical Sciences which provided an excellent environment for ?nishing the work on the book. My thanks also go to Vladimir Zaiats for his highly competent translation of the French original into English and to John Kimmel for being a very supportive and patient editor. Alexandre Tsybakov Paris, June 2008 Preface to the French Edition The tradition of considering the problem of statistical estimation as that of estimation of a ?nite number of parameters goes back to Fisher.However, parametric models provide only an approximation, often imprecise, of the - derlying statistical structure. Statistical models that explain the data in a more consistent way are often more complex: Unknown elements in these models are, in general, some functions having certain properties of smoo- ness. Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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