Weak dependence with examples and applications
This monograph is aimed at developing Doukhan/Louhichi's (1999) idea to measure asymptotic independence of a random process. The authors propose various examples of models fitting such conditions such as stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovia...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
New York :
Springer
c2007.
|
| Edición: | 1st ed. 2007. |
| Colección: | Lecture notes in statistics (Springer-Verlag) ;
v.190. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009461419806719 |
Tabla de Contenidos:
- Weak dependence
- Models
- Tools for non causal cases
- Tools for causal cases
- Applications of strong laws of large numbers
- Central Limit theorem
- Donsker Principles
- Law of the iterated logarithm (LIL)
- The Empirical process
- Functional estimation
- Spectral estimation
- Econometric applications and resampling.
