Overview
- Provides a unified overview of Bartlett corrections and bias reduction
- Discusses bootstrap-based inference
- Includes applications to important statistical models
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents (4 chapters)
Keywords
About this book
This book presents a concise introduction to Bartlett and Bartlett-type corrections of statistical tests and bias correction of point estimators. The underlying idea behind both groups of corrections is to obtain higher accuracy in small samples. While the main focus is on corrections that can be analytically derived, the authors also present alternative strategies for improving estimators and tests based on bootstrap, a data resampling technique and discuss concrete applications to several important statistical models.
Reviews
From the book reviews:
“This monograph endeavors to give a review of research on the topic of Bartlett and Bartlett-type corrections that can be applied to test statistics as well as bias corrections of maximum likelihood estimators. The authors have written an interesting book, which is intended to serve the need of researchers and graduate students in statistics. The book could also be very useful as a supplement for graduate level courses among others in statistical inference.” (Apostolos Batsidis, zbMATH 1306.62025, 2015)
Authors and Affiliations
About the authors
Gauss M. Cordeiro is a Professor of Statistics at Universidade Federal de Pernambuco in Brazil. He is a former chief editor of the Brazilian Journal of Probability and Statistics and a former president of the Brazilian Statistical Association.
Francisco Cribari-Neto is a Professor of Statistics at Universidade Federal de Pernambuco in Brazil. He is a former applications editor of the Brazilian Journal of Probability and Statistics and a former president of the Brazilian Econometric Society.
Bibliographic Information
Book Title: An Introduction to Bartlett Correction and Bias Reduction
Authors: Gauss M. Cordeiro, Francisco Cribari-Neto
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-642-55255-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2014
Softcover ISBN: 978-3-642-55254-0Published: 20 May 2014
eBook ISBN: 978-3-642-55255-7Published: 08 May 2014
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: XI, 107
Topics: Statistical Theory and Methods, Econometrics, Statistics for Business, Management, Economics, Finance, Insurance