Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)
Language: English
Published by Springer, 2015
- Softcover
- Used
Seller: Pangea, Louisville, KY, U.S.A.Pangea
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- Title
- Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)
- Author
- Boos, Dennis D. D.; Stefanski, L A
- Publisher
- Springer
- Publication year
- 2015
- Condition
- Good
- Binding
- paperback
- Language
- English
- ISBN 10
- 1489987932
- ISBN 13
- 9781489987938
- Item weight
- 29 ounces
- Dimensions
- 6x1x9
- Series
- Book 67 of 111: Springer Texts in Statistics
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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