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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Doukhan, Paul (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Σειρά:Mathématiques et Applications, 80
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.