A Graduate Course on Statistical Inference

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Synopsis

This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.

Book details

Edition:
1st ed. 2019
Series:
Springer Texts in Statistics
Author:
Bing Li, G. Jogesh Babu
ISBN:
9781493997619
Related ISBNs:
9781493997596
Publisher:
Springer New York
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2021-02-01
Usage restrictions:
Copyright
Copyright date:
2019
Copyright by:
Springer Science+Business Media, LLC 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Nonfiction