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...
Enregistré dans:
| Auteur principal: | |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
New York, NY :
Springer New York
2010.
Cham : Springer Nature |
| Collection: | Springer Texts in Statistics
|
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Theoretical Statistics, Texte imprimé, 9780387939902 • Theoretical statistics, topics for a core course, Robert W. Keener, New York, Springer, 2010, 1 vol. (XVIII-538 p.), Springer texts in statistics, 978-0-387-93838-7 • Theoretical statistics, topics for a core course, Robert W. Keener, New York, Springer, 2010, 1 vol. (XVIII-538 p.), Springer texts in statistics, 978-0-387-93838-7 |
Table des matières:
- 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 Optimality1
- Large-Sample Theory for Likelihood Ratio Tests
- Nonparametric Regression
- Bootstrap Methods
- Sequential Methods.