Essential Statistical Inference: Theory and Methods - Couverture rigide
Livre 65 sur 103: Springer Texts in Statistics
Synopsis
This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems.
An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology.
Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)
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Springer (edition 2013), 2013
ISBN 10 : 1461448174
ISBN 13 : 9781461448174
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Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)
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Springer, 2013
ISBN 10 : 1461448174
ISBN 13 : 9781461448174
Ancien ou d'occasion
Couverture rigide
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Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)
Edité par
Springer, 2013
ISBN 10 : 1461448174
ISBN 13 : 9781461448174
Ancien ou d'occasion
Couverture rigide
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Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics)
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Springer, 2013
ISBN 10 : 1461448174
ISBN 13 : 9781461448174
Ancien ou d'occasion
Couverture rigide
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Essential Statistical Inference
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ISBN 10 : 1461448174
ISBN 13 : 9781461448174
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Valuable text for graduate students and reference for researchersContains R code throughout the text and in sample problems Includes unique page references to equation displaysDennis Boos and Len Stefanski are professors in the Depa. N° de réf. du vendeur 4198548
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Essential Statistical Inference
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Springer New York, Springer US Feb 2013, 2013
ISBN 10 : 1461448174
ISBN 13 : 9781461448174
Neuf
Couverture rigide
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems.An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology.Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods. 588 pp. Englisch. N° de réf. du vendeur 9781461448174
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Essential Statistical Inference | Theory and Methods
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Buch. Etat : Neu. Essential Statistical Inference | Theory and Methods | L A Stefanski (u. a.) | Buch | xvii | Englisch | 2013 | Springer US | EAN 9781461448174 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 106403237
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Essential Statistical Inference
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Essential Statistical Inference
Edité par
Springer New York, Springer US Feb 2013, 2013
ISBN 10 : 1461448174
ISBN 13 : 9781461448174
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -¿This book is for students and researchers who have had a first year graduate level mathematicalstatistics course. It covers classical likelihood, Bayesian, and permutation inference;an introduction to basic asymptotic distribution theory; and modern topics like M-estimation,the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large numberof examples and problems.An important goal has been to make the topics accessible to a wide audience, with little overt relianceon measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimationand testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology.Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State.Their research has been eclectic, often with a robustness angle, although Stefanski is also known forresearch concentrated on measurement error, including a co-authored book on non-linear measurementerror models. In recent years the authors have jointly worked on variable selection methods.¿Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 588 pp. Englisch. N° de réf. du vendeur 9781461448174
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