Stochastic Models for Time Series
This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap ar...
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| Otros Autores: | |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer
2018.
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| Colección: | Mathématiques et Applications,
80. Springer eBooks. |
| Acceso en línea: | Conectar con la versión electrónica |
| Ver en Universidad de Navarra: | https://innopac.unav.es/record=b38029595*spi |
Tabla de Contenidos:
- Part I Independence and Stationarity
- 1 Probability and Independence
- 2 Gaussian convergence and inequalities
- 3 Estimation concepts
- 4 Stationarity
- Part II Models of time series
- 5 Gaussian chaos
- 6 Linear processes
- 7 Non-linear processes
- 8 Associated processes
- Part III Dependence
- 9 Dependence
- 10 Long-range dependence
- 11 Short-range dependence
- 12 Moments and cumulants
- Appendices
- A Probability and distributions
- B Convergence and processes
- C R scripts used for the gures
- Index- List of figures.
