Essential Statistical Inference Theory and Methods /

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 th...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Boos, Dennis D. (Author), Stefanski, L A. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: New York, NY : Springer New York : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Springer Texts in Statistics, 120
Subjects:
Statistics .
Mathematical statistics-Data processing.
Statistical Theory and Methods.
Statistics.
Statistics and Computing.
Online Access:Texto Completo
Table of Contents:
  • 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.

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