Introduction to Time Series Modeling
eBook - PDF

Introduction to Time Series Modeling

  1. 296 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Introduction to Time Series Modeling

About this book

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very im

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Yes, you can access Introduction to Time Series Modeling by Genshiro Kitagawa in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title
  3. Copyright
  4. Preface
  5. List of Figures
  6. List of Tables
  7. Contents
  8. Chapter 1: Introduction and Preparatory Analysis
  9. Chapter 2: The Covariance Function
  10. Chapter 3: The Power Spectrum and the Periodogram
  11. Chapter 4: Statistical Modeling
  12. Chapter 5: The Least Squares Method
  13. Chapter 6: Analysis of Time Series Using ARMA Models
  14. Chapter 7: Estimation of an AR Model
  15. Chapter 8: The Locally Stationary AR Model
  16. Chapter 9: Analysis of Time Series with a State-Space Model
  17. Chapter 10: Estimation of the ARMA Model
  18. Chapter 11: Estimation of Trends
  19. Chapter 12: The Seasonal Adjustment Model
  20. Chapter 13: Time-Varying Coefficient AR Model
  21. Chapter 14: Non-Gaussian State-Space Model
  22. Chapter 15: The Sequential Monte Carlo Filter
  23. Chapter 16: Simulation
  24. Appendix A: Algorithms for Nonlinear Optimization
  25. Appendix B: Derivation of Levinson’s Algorithm
  26. Appendix C: Derivation of the Kalman Filter and Smoother Algorithms
  27. Appendix D: Algorithm for the Monte Carlo Filter
  28. Answers to the Problems
  29. Bibliography
  30. Index
  31. Back Cover