Empirical Processes in M-Estimation

Klappentext Advanced text; estimation methods in statistics, e.g. least squares; lots of examples; minimal abstraction. Zusammenfassung This book deals with estimation methods in statistics! and treats various models in a unified way. Many illustrative examples are given! including the Grenander estimator! smoothing splines! partially linear models! mixture models and image analysis. Graduate students and professionals in statistics will welcome this treatment. Inhaltsverzeichnis Preface; Reading guide; 1. Introduction; 2. Notations and definitions; 3. Uniform laws of large numbers; 4. First applications: consistency; 5. Increments of empirical processes; 6. Central limit theorems; 7. Rates of convergence for maximum likelihood estimators; 8. The non-i.i.d. case; 9. Rates of convergence for least squares estimators; 10. Penalties and sieves; 11. Some applications to semi-parametric models; 12. M-estimators; Appendix; References; Author index; Subject index; List of symbols.

Product details

• Authors: Sara a. van de Geer, Sara A. Van De Geer, Sara A. Van De Geer
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Paperback / Softback
• Released: 19.11.2009
• EAN: 9780521123259
• ISBN: 978-0-521-12325-9
• No. of pages: 300
• Series: Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge Series in Statistica
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics