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All of Nonparametric Statistics (Springer Texts in Statistics)
Book 24 of 111: Springer Texts in StatisticsSeller: Bay State Book Company, North Smithfield, RI, U.S.A.
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All of Nonparametric Statistics (Springer Texts in Statistics)
Book 24 of 111: Springer Texts in StatisticsSeller: Ria Christie Collections, Uxbridge, United Kingdom
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£ 96.88
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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All of Nonparametric Statistics (Springer Texts in Statistics)
Book 24 of 111: Springer Texts in StatisticsSeller: Ria Christie Collections, Uxbridge, United Kingdom
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£ 127.60
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Taschenbuch. Condition: Neu. All of Nonparametric Statistics | Larry Wasserman | Taschenbuch | Springer Texts in Statistics | xii | Englisch | 2010 | Humana | EAN 9781441920447 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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£ 141.99
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Paperback. Condition: Brand New. 268 pages. 8.80x5.90x0.90 inches. In Stock.
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Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsLanguage: English
Published by Springer-Verlag New York Inc., US, 2005
ISBN 10: 0387251456 ISBN 13: 9780387251455
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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Add to basketHardback. Condition: New. 1st ed. 2005. Corr. 3rd. printing 2007. The goal of this text is to provide the reader with a single book where they can find a brief account of many, modern topics in nonparametric inference. The book is aimed at Master's level or Ph. D. level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. This text covers a wide range of topics including: the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book has a mixture of methods and theory.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to nd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can nd a brief account of many of the modern topics in nonparametric inference. The book is aimed at master's-level or Ph. D. -level statistics and computer science students. It is also suitable for researchersin statistics, machine lea- ing and data mining who want to get up to speed quickly on modern n- parametric methods. My goal is to quickly acquaint the reader with the basic concepts in many areas rather than tackling any one topic in great detail. In the interest of covering a wide range of topics, while keeping the book short, I have opted to omit most proofs. Bibliographic remarks point the reader to references that contain further details. Of course, I have had to choose topics to include andto omit,the title notwithstanding. For the mostpart,I decided to omit topics that are too big to cover in one chapter. For example, I do not cover classi cation or nonparametric Bayesian inference. The book developed from my lecture notes for a half-semester (20 hours) course populated mainly by master's-level students. For Ph. D.
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Condition: As New. Unread book in perfect condition.
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Condition: New. pp. 284.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condition: As New. Unread book in perfect condition.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to nd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can nd a brief account of many of the modern topics in nonparametric inference. The book is aimed at master's-level or Ph. D. -level statistics and computer science students. It is also suitable for researchersin statistics, machine lea- ing and data mining who want to get up to speed quickly on modern n- parametric methods. My goal is to quickly acquaint the reader with the basic concepts in many areas rather than tackling any one topic in great detail. In the interest of covering a wide range of topics, while keeping the book short, I have opted to omit most proofs. Bibliographic remarks point the reader to references that contain further details. Of course, I have had to choose topics to include andto omit,the title notwithstanding. For the mostpart,I decided to omit topics that are too big to cover in one chapter. For example, I do not cover classi cation or nonparametric Bayesian inference. The book developed from my lecture notes for a half-semester (20 hours) course populated mainly by master's-level students. For Ph. D.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsLanguage: English
Published by Springer-Verlag New York Inc., US, 2005
ISBN 10: 0387251456 ISBN 13: 9780387251455
£ 152.40
£ 65 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. 1st ed. 2005. Corr. 3rd. printing 2007. The goal of this text is to provide the reader with a single book where they can find a brief account of many, modern topics in nonparametric inference. The book is aimed at Master's level or Ph. D. level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. This text covers a wide range of topics including: the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book has a mixture of methods and theory.
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Condition: new. Questo è un articolo print on demand.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsLanguage: English
Published by Springer, Humana Nov 2010, 2010
ISBN 10: 1441920447 ISBN 13: 9781441920447
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to nd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can nd a brief account of many of the modern topics in nonparametric inference. The book is aimed at master's-level or Ph. D. -level statistics and computer science students. It is also suitable for researchersin statistics, machine lea- ing and data mining who want to get up to speed quickly on modern n- parametric methods. My goal is to quickly acquaint the reader with the basic concepts in many areas rather than tackling any one topic in great detail. In the interest of covering a wide range of topics, while keeping the book short, I have opted to omit most proofs. Bibliographic remarks point the reader to references that contain further details. Of course, I have had to choose topics to include andto omit,the title notwithstanding. For the mostpart,I decided to omit topics that are too big to cover in one chapter. For example, I do not cover classi cation or nonparametric Bayesian inference. The book developed from my lecture notes for a half-semester (20 hours) course populated mainly by master's-level students. For Ph. D. 284 pp. Englisch.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsLanguage: English
Published by Springer-Verlag New York Inc., 2010
ISBN 10: 1441920447 ISBN 13: 9781441920447
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 114.97
£ 15.33 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. There are many books on various aspects of nonparametric inference but no other book covers all the topics in one placeOffers a brief account of the modern topics in nonparametric inferenceThis text provides the reader with a single boo.
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All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsLanguage: English
Published by Springer, Humana Nov 2010, 2010
ISBN 10: 1441920447 ISBN 13: 9781441920447
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to nd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can nd a brief account of many of the modern topics in nonparametric inference. The book is aimed at masterżs-level or Ph. D. -level statistics and computer science students. It is also suitable for researchersin statistics, machine lea- ing and data mining who want to get up to speed quickly on modern n- parametric methods. My goal is to quickly acquaint the reader with the basic concepts in many areas rather than tackling any one topic in great detail. In the interest of covering a wide range of topics, while keeping the book short, I have opted to omit most proofs. Bibliographic remarks point the reader to references that contain further details. Of course, I have had to choose topics to include andto omit,the title notwithstanding. For the mostpart,I decided to omit topics that are too big to cover in one chapter. For example, I do not cover classi cation or nonparametric Bayesian inference. The book developed from my lecture notes for a half-semester (20 hours) course populated mainly by masterżs-level students. For Ph. D.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 284 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. There are many books on various aspects of nonparametric inference but no other book covers all the topics in one placeOffers a brief account of the modern topics in nonparametric inferenceThis text provides the reader with a single boo.
-
All of Nonparametric Statistics
Book 24 of 111: Springer Texts in StatisticsLanguage: English
Published by Springer, Humana Okt 2005, 2005
ISBN 10: 0387251456 ISBN 13: 9780387251455
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to nd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can nd a brief account of many of the modern topics in nonparametric inference. The book is aimed at master's-level or Ph. D. -level statistics and computer science students. It is also suitable for researchersin statistics, machine lea- ing and data mining who want to get up to speed quickly on modern n- parametric methods. My goal is to quickly acquaint the reader with the basic concepts in many areas rather than tackling any one topic in great detail. In the interest of covering a wide range of topics, while keeping the book short, I have opted to omit most proofs. Bibliographic remarks point the reader to references that contain further details. Of course, I have had to choose topics to include andto omit,the title notwithstanding. For the mostpart,I decided to omit topics that are too big to cover in one chapter. For example, I do not cover classi cation or nonparametric Bayesian inference. The book developed from my lecture notes for a half-semester (20 hours) course populated mainly by master's-level students. For Ph. D. 284 pp. Englisch.
