Time Series

Time Series

by Raquel Prado, Mike West
Released May 2010
Publisher(s): Chapman and Hall/CRC
ISBN: 9781439882757

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Book description

Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian t

Table of contents

  1. Front cover (1/2)
  2. Front cover (2/2)
  3. Contents (1/2)
  4. Contents (2/2)
  5. Preface
  6. Chapter 1: Notation, definitions, and basic inference (1/7)
  7. Chapter 1: Notation, definitions, and basic inference (2/7)
  8. Chapter 1: Notation, definitions, and basic inference (3/7)
  9. Chapter 1: Notation, definitions, and basic inference (4/7)
  10. Chapter 1: Notation, definitions, and basic inference (5/7)
  11. Chapter 1: Notation, definitions, and basic inference (6/7)
  12. Chapter 1: Notation, definitions, and basic inference (7/7)
  13. Chapter 2: Traditional time domain models (1/11)
  14. Chapter 2: Traditional time domain models (2/11)
  15. Chapter 2: Traditional time domain models (3/11)
  16. Chapter 2: Traditional time domain models (4/11)
  17. Chapter 2: Traditional time domain models (5/11)
  18. Chapter 2: Traditional time domain models (6/11)
  19. Chapter 2: Traditional time domain models (7/11)
  20. Chapter 2: Traditional time domain models (8/11)
  21. Chapter 2: Traditional time domain models (9/11)
  22. Chapter 2: Traditional time domain models (10/11)
  23. Chapter 2: Traditional time domain models (11/11)
  24. Chapter 3: The frequency domain (1/7)
  25. Chapter 3: The frequency domain (2/7)
  26. Chapter 3: The frequency domain (3/7)
  27. Chapter 3: The frequency domain (4/7)
  28. Chapter 3: The frequency domain (5/7)
  29. Chapter 3: The frequency domain (6/7)
  30. Chapter 3: The frequency domain (7/7)
  31. Chapter 4: Dynamic linear models (1/6)
  32. Chapter 4: Dynamic linear models (2/6)
  33. Chapter 4: Dynamic linear models (3/6)
  34. Chapter 4: Dynamic linear models (4/6)
  35. Chapter 4: Dynamic linear models (5/6)
  36. Chapter 4: Dynamic linear models (6/6)
  37. Chapter 5: State-space TVAR models (1/4)
  38. Chapter 5: State-space TVAR models (2/4)
  39. Chapter 5: State-space TVAR models (3/4)
  40. Chapter 5: State-space TVAR models (4/4)
  41. Chapter 6: General state-space models andsequential Monte Carlo methods (1/6)
  42. Chapter 6: General state-space models andsequential Monte Carlo methods (2/6)
  43. Chapter 6: General state-space models andsequential Monte Carlo methods (3/6)
  44. Chapter 6: General state-space models andsequential Monte Carlo methods (4/6)
  45. Chapter 6: General state-space models andsequential Monte Carlo methods (5/6)
  46. Chapter 6: General state-space models andsequential Monte Carlo methods (6/6)
  47. Chapter 7: Mixture models in time series (1/9)
  48. Chapter 7: Mixture models in time series (2/9)
  49. Chapter 7: Mixture models in time series (3/9)
  50. Chapter 7: Mixture models in time series (4/9)
  51. Chapter 7: Mixture models in time series (5/9)
  52. Chapter 7: Mixture models in time series (6/9)
  53. Chapter 7: Mixture models in time series (7/9)
  54. Chapter 7: Mixture models in time series (8/9)
  55. Chapter 7: Mixture models in time series (9/9)
  56. Chapter 8: Topics and examples in multipletime series (1/4)
  57. Chapter 8: Topics and examples in multipletime series (2/4)
  58. Chapter 8: Topics and examples in multipletime series (3/4)
  59. Chapter 8: Topics and examples in multipletime series (4/4)
  60. Chapter 9: Vector AR and ARMA models (1/3)
  61. Chapter 9: Vector AR and ARMA models (2/3)
  62. Chapter 9: Vector AR and ARMA models (3/3)
  63. Chapter 10: Multivariate DLMs and covariance models (1/12)
  64. Chapter 10: Multivariate DLMs and covariance models (2/12)
  65. Chapter 10: Multivariate DLMs and covariance models (3/12)
  66. Chapter 10: Multivariate DLMs and covariance models (4/12)
  67. Chapter 10: Multivariate DLMs and covariance models (5/12)
  68. Chapter 10: Multivariate DLMs and covariance models (6/12)
  69. Chapter 10: Multivariate DLMs and covariance models (7/12)
  70. Chapter 10: Multivariate DLMs and covariance models (8/12)
  71. Chapter 10: Multivariate DLMs and covariance models (9/12)
  72. Chapter 10: Multivariate DLMs and covariance models (10/12)
  73. Chapter 10: Multivariate DLMs and covariance models (11/12)
  74. Chapter 10: Multivariate DLMs and covariance models (12/12)
  75. Bibliography (1/4)
  76. Bibliography (2/4)
  77. Bibliography (3/4)
  78. Bibliography (4/4)
  79. Author Index (1/2)
  80. Author Index (2/2)
  81. Subject Index (1/2)
  82. Subject Index (2/2)
  83. Back cover

Product information

  • Title: Time Series
  • Author(s): Raquel Prado, Mike West
  • Release date: May 2010
  • Publisher(s): Chapman and Hall/CRC
  • ISBN: 9781439882757