Essential Statistical Inference : Theory and Methods
Boos, Dennis D; Stefanski, Leonard a
ISBN 10: 1489987932 ISBN 13: 9781489987938
Editorial: Springer, 2015
Nuevos
Encuadernación de tapa blanda
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Calificación del vendedor: 5 de 5 estrellas
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Descripción
Descripción:
N° de ref. del artículo 23411387-n
Sinopsis:
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.
Acerca del autor: 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.
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Título: Essential Statistical Inference : Theory and...
Editorial: Springer
Año de publicación: 2015
Encuadernación: Encuadernación de tapa blanda
Condición: New
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paperback. Condición: Good. May contain marks and or highlighting. Used items are NOT guaranteed to include components, i.e. CDs, Access codes, etc. Ships from our Kentucky facility. Ships same day if ordered before 1 PM EST, Monday - Friday. Contact us with any questions! Nº de ref. del artículo: 264217-1
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Springer New York, Springer US Mär 2015, 2015
ISBN 10: 1489987932
ISBN 13: 9781489987938
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781489987938
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Essential Statistical Inference
Publicado por
Springer New York, Springer US Mär 2015, 2015
ISBN 10: 1489987932
ISBN 13: 9781489987938
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781489987938
Cantidad disponible: 2 disponibles
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Essential Statistical Inference : Theory and Methods
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