Stefanski / Boos | Essential Statistical Inference | Buch | 978-1-4899-8793-8 | sack.de

Buch, Englisch, 568 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 8774 g

Reihe: Springer Texts in Statistics

Stefanski / Boos

Essential Statistical Inference

Theory and Methods
2013
ISBN: 978-1-4899-8793-8
Verlag: Springer

Theory and Methods

Buch, Englisch, 568 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 8774 g

Reihe: Springer Texts in Statistics

ISBN: 978-1-4899-8793-8
Verlag: Springer


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. 

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Zielgruppe


Graduate

Weitere Infos & Material


Roles of Modeling in Statistical Inference.- Likelihood Construction and Estimation.- Likelihood-Based Tests and Confidence Regions.- Bayesian Inference.- Large Sample Theory: The Basics.- Large Sample Results for Likelihood-Based Methods.- M-Estimation (Estimating Equations).- Hypothesis Tests under Misspecification and Relaxed Assumptions.- Monte Carlo Simulation Studies.- Jackknife.- Bootstrap.- Permutation and Rank Tests.- Appendix: Derivative Notation and Formulas.- References.- Author Index.- Example Index.- R-code Index.- Subject Index.


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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