A Graduate Course on Statistical Inference

• Main Authors: Li, Bing (Author, http://id.loc.gov/vocabulary/relators/aut), Babu, G. Jogesh (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Springer Texts in Statistics,
• Subjects: Statistics .; Statistical Theory and Methods.

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...

Table of Contents:

• 1. Probability and Random Variables
• 2. Classical Theory of Estimation
• 3. Testing Hypotheses in the Presence of Nuisance Parameters
• 4. Testing Hypotheses in the Presence of Nuisance Parameters
• 5. Basic Ideas of Bayesian Methods
• 6. Bayesian Inference
• 7. Asymptotic Tools and Projections
• 8. Asymptotic Theory for Maximum Likelihood Estimation
• 9. Estimating Equations
• 10. Convolution Theorem and Asymptotic Efficiency
• 11. Asymptotic Hypothesis Test
• References
• Index.