Stochastic Models for Time Series

• Main Author: Doukhan, Paul (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Mathématiques et Applications, 80
• Subjects: Statistics .; Probabilities.; Econometrics.; Dynamics.; Ergodic theory.; Statistical Theory and Methods.; Probability Theory and Stochastic Processes.; Dynamical Systems and Ergodic Theory.

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...

Table of Contents:

• 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.