Statistical inference and asymptotic theory for stationary time series 定常時系列に対する統計的推測と漸近理論

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Author

    • 柿沢, 佳秀 カキザワ, ヨシヒデ

Bibliographic Information

Title

Statistical inference and asymptotic theory for stationary time series

Other Title

定常時系列に対する統計的推測と漸近理論

Author

柿沢, 佳秀

Author(Another name)

カキザワ, ヨシヒデ

University

大阪大学

Types of degree

博士 (理学)

Grant ID

甲第5649号

Degree year

1996-03-25

Note and Description

博士論文

Table of Contents

  1. Contents / p1 (0003.jp2)
  2. 1 Introduction / p1 (0006.jp2)
  3. 2 Asymptotic efficiency of the sample covariances in Gaussian stationary processes / p4 (0009.jp2)
  4. 2.1 Introduction / p4 (0009.jp2)
  5. 2.2 Asymptotic variance and Cramer-Rao bound / p5 (0010.jp2)
  6. 2.3 Asymptotic efficiency of sample covariances / p7 (0012.jp2)
  7. 2.4 The case of vector sample autocovariances / p9 (0014.jp2)
  8. 3 Third order asymptotic propertiesof estimators inGaussian ARMA processes with unknown mean / p11 (0016.jp2)
  9. 3.1 Introduction / p11 (0016.jp2)
  10. 3.2 Third order asymptotic efficiency of MLE in ARMA(p,q|μ,σ²) / p12 (0017.jp2)
  11. 3.3 Third order asymptotic properties of estimators in AR(1|μ,σ²) / p14 (0019.jp2)
  12. 3.4 Simulation results / p16 (0021.jp2)
  13. 3.5 Appendix:Stochastic expansion of MLE of ρ / p16 (0021.jp2)
  14. 4 Saddlepoint approximations for time series statistics / p18 (0023.jp2)
  15. 4.1 Introduction / p18 (0023.jp2)
  16. 4.2 Edgeworth and saddlepoint approximations / p19 (0024.jp2)
  17. 4.3 Saddlepoint approximations in the center of the distribution, using pertur- bated saddlepoint / p21 (0026.jp2)
  18. 4.4 Numerical examples / p22 (0027.jp2)
  19. 4.5 Appendix:Approximation for density of [数式] / p25 (0030.jp2)
  20. 5 Valid Edgeworth expansions of some estimators in non-Gaussian AR(1) process / p28 (0033.jp2)
  21. 5.1 Introduction / p28 (0033.jp2)
  22. 5.2 Preliminaries / p28 (0033.jp2)
  23. 5.3 Basic Theorems / p30 (0035.jp2)
  24. 5.4 Application to confidence intervals / p31 (0036.jp2)
  25. 5.5 Simulation results / p34 (0039.jp2)
  26. 5.6 Appendix / p38 (0043.jp2)
  27. 6 Discriminant analysis for stationary processes / p45 (0050.jp2)
  28. 6.1 Introduction / p45 (0050.jp2)
  29. 6.2 Disparity measure between spectral densities / p46 (0051.jp2)
  30. 6.3 Discriminant analysis in multivariate stationary processes:nonparametric approach / p48 (0053.jp2)
  31. 6.4 Discriminant analysis in scalar Gaussian stationary processes:parametric approach / p52 (0057.jp2)
  32. 6.5 Appendix / p59 (0064.jp2)
  33. 7 Parameter estimation and testing in stationary vector time series,using the spectral disparity measure / p63 (0068.jp2)
  34. 7.1 Introduction / p63 (0068.jp2)
  35. 7.2 The central limit theorem / p64 (0069.jp2)
  36. 7.3 Hypothesis testing of spectral parameters / p69 (0074.jp2)
  37. 8 Peak-insensitive estimation and hypothesis testing of integral of non- linear function of spectral density / p72 (0077.jp2)
  38. 8.1 Introduction / p72 (0077.jp2)
  39. 8.2 Preliminaries / p73 (0078.jp2)
  40. 8.3 Main results on asymptotic normality / p75 (0080.jp2)
  41. 8.4 Applications / p77 (0082.jp2)
  42. 8.5 Appendix:Proofs / p81 (0086.jp2)
  43. Acknowledgments / p89 (0094.jp2)
  44. References / p90 (0095.jp2)
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Codes

  • NII Article ID (NAID)
    500000130541
  • NII Author ID (NRID)
    • 8000000954289
  • DOI(NDL)
  • Text Lang
    • und
  • NDLBibID
    • 000000294855
  • Source
    • Institutional Repository
    • NDL ONLINE
    • NDL Digital Collections

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