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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著者

    • 柿沢, 佳秀 カキザワ, ヨシヒデ

書誌事項

タイトル

Statistical inference and asymptotic theory for stationary time series

タイトル別名

定常時系列に対する統計的推測と漸近理論

著者名

柿沢, 佳秀

著者別名

カキザワ, ヨシヒデ

学位授与大学

大阪大学

取得学位

博士 (理学)

学位授与番号

甲第5649号

学位授与年月日

1996-03-25

注記・抄録

博士論文

14401甲第05649号

博士(理学)

大阪大学

1996-03-25

12546

目次

  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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各種コード

  • NII論文ID(NAID)
    500000130541
  • NII著者ID(NRID)
    • 8000000954289
  • DOI(NDL)
  • NDL書誌ID
    • 000000294855
  • データ提供元
    • 機関リポジトリ
    • NDL-OPAC
    • NDLデジタルコレクション
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