A Graduate Course on Statistical Inference
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