Theoretical statistics topics for a core course /
Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the n...
| Main Author: | Keener, Robert W., |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
[2010]
|
| Physical Description: |
1 online resource (xvii, 538 pages) : illustrations. |
| Series: |
Springer texts in statistics.
|
| Subjects: |
Table of Contents:
- Probability and measure
- Exponential families
- Risk, sufficiency, completeness, and ancillarity
- Unbiased estimation
- Curved exponential families
- Conditional distributions
- Bayesian estimation
- Large sample theory
- Estimating equations and maximum likelihood
- Equivariant estimation
- Empirical bayes and shrinkage estimators
- Hypothesis testing
- Optimal tests in higher dimensions
- General linear model
- Bayesian inference: Modeling and computation
- Asymptotic optimality
- Large sample theory for likelihood ratio tests
- Nonparametric regression
- Bootstrap methods
- Sequential methods.