Articles liés à All of Nonparametric Statistics
Synopsis
Aimed at Masters or PhD level students in statistics, computer science, and engineering, this comprehensive text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference, all set out with exceptional clarity. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. With an exhaustive exploration of asymptotic nonparametric inferences, it also covers a huge range of other crucial topic areas including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book's dual approach includes a mixture of methodology and theory.
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Présentation de l'éditeur
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. From the reviews: "...The book is excellent." (Short Book Reviews of the ISI, June 2006) "Now we have All of Nonparametric Statistics … . the writing is excellent and the author is to be congratulated on the clarity achieved. … the book is excellent." (N.R. Draper, Short Book Reviews, Vol. 26 (1), 2006) "Overall, I enjoyed reading this book very much. I like Wasserman's intuitive explanations and careful insights into why one path or approach is taken over another. Most of all, I am impressed with the wealth of information on the subject of asymptotic nonparametric inferences." (Stergios B. Fotopoulos for Technometrics, Vol. 49, No. 1., February 2007)
Revue de presse
"Now we have All of Nonparametric Statistics ... the writing is excellent and the author is to be congratulated on the clarity achieved. ... the book is excellent." --N.R. Draper, Short Book Reviews, 26:1, 2006
"Overall, I enjoyed reading this book very much. I like Wasserman's intuitive explanations and careful insights into why one path or approach is taken over another. Most of all, I am impressed with the wealth of information on the subject of asymptotic nonparametric inferences." --Stergios B. Fotopoulos for Technometrics, 49:1, February 2007
"...ANPS provides an excellent complement or a complete course textbook with a mixture of theoretical and computational exercises. ...For a book in a rapidly evolving field, the content and references are quit eup to date. ...As advertised, it offers a well-written, albeit brief account of numerous topics in modern nonparametric inference." --Greg Ridgeway, Journal of the American Statistical Association, Vol. 102, No. 477, 2007
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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All of Nonparametric Statistics (Springer Texts in Statistics)
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All of Nonparametric Statistics: A Concise Course in Nonparametric Statistical Inference (Springer Texts in Statistics)
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All of Nonparametric Statistics
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Gebunden. Etat : 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. N° de réf. du vendeur 5909447
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All of Nonparametric Statistics (Springer Texts in Statistics)
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All of Nonparametric Statistics
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All of Nonparametric Statistics
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Springer New York Okt 2005, 2005
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ISBN 13 : 9780387251455
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Buch. Etat : 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. N° de réf. du vendeur 9780387251455
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All of Nonparametric Statistics (Springer Texts in Statistics)
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All of Nonparametric Statistics
Edité par
Springer, 2005
ISBN 10 : 0387251456
ISBN 13 : 9780387251455
Ancien ou d'occasion
Couverture rigide
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All of Nonparametric Statistics
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Springer New York, Springer US, 2005
ISBN 10 : 0387251456
ISBN 13 : 9780387251455
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : 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. N° de réf. du vendeur 9780387251455
Quantité disponible : 1 disponible(s)
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All of Nonparametric Statistics
Edité par
Springer New York, Springer US Okt 2005, 2005
ISBN 10 : 0387251456
ISBN 13 : 9780387251455
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 284 pp. Englisch. N° de réf. du vendeur 9780387251455
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