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Essential Statistical Inference: Theory and Methods
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Catalogue Information
Field name
Details
Dewey Class
519.5
Title
Essential Statistical Inference ([Ebook]) : Theory and Methods / by Dennis D. Boos, L. A. Stefanski.
Author
Boos, Dennis D.
Added Personal Name
Stefanski, L. A.
Other name(s)
SpringerLink (Online service)
Publication
New York, NY : Springer
, 2013.
Physical Details
XVII, 568 pages: 34 illus. : online resource.
Series
Springer Texts in Statistics
1431-875X ; ; 120
ISBN
9781461448181
Summary Note
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. :
Contents note
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. .
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site
http://dx.doi.org/10.1007/978-1-4614-4818-1
Links to Related Works
Subject References:
Mathematical Statistics
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Statistical Theory and Methods
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Statistics
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Statistics and Computing/Statistics Programs
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Statistics, general
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Authors:
author
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Boos, Dennis D.
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Stefanski, L. A.
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Corporate Authors:
SpringerLink (Online service)
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Series:
Springer Texts in Statistics
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Classification:
519.5
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519.5 (DDC 23)
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