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Advances in Decision Sciences
Volume 2012 (2012), Article ID 515494, 11 pages
http://dx.doi.org/10.1155/2012/515494
Research Article

Asymptotic Optimality of Estimating Function Estimator for CHARN Model

Faculty of Economics, Wakayama University, 930 Sakaedani, Wakayama 640-8510, Japan

Received 15 February 2012; Accepted 9 April 2012

Academic Editor: Hiroshi Shiraishi

Copyright © 2012 Tomoyuki Amano. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. T. Amano and M. Taniguchi, “Asymptotic efficiency of conditional least squares estimators for ARCH models,” Statistics & Probability Letters, vol. 78, no. 2, pp. 179–185, 2008. View at Publisher · View at Google Scholar
  2. V. P. Godambe, “An optimum property of regular maximum likelihood estimation,” Annals of Mathematical Statistics, vol. 31, pp. 1208–1211, 1960. View at Publisher · View at Google Scholar
  3. V. P. Godambe, “The foundations of finite sample estimation in stochastic processes,” Biometrika, vol. 72, no. 2, pp. 419–428, 1985. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  4. L. P. Hansen, “Large sample properties of generalized method of moments estimators,” Econometrica, vol. 50, no. 4, pp. 1029–1054, 1982. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  5. S. A. Chandra and M. Taniguchi, “Estimating functions for nonlinear time series models,” Annals of the Institute of Statistical Mathematics, vol. 53, no. 1, pp. 125–141, 2001. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  6. T. Amano, “Asymptotic efficiency of estimating function estimators for nonlinear time series models,” Journal of the Japan Statistical Society, vol. 39, no. 2, pp. 209–231, 2009. View at Google Scholar
  7. W. Härdle and A. Tsybakov, “Local polynomial estimators of the volatility function in nonparametric autoregression,” Journal of Econometrics, vol. 81, no. 1, pp. 223–242, 1997. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  8. W. Härdle, A. Tsybakov, and L. Yang, “Nonparametric vector autoregression,” Journal of Statistical Planning and Inference, vol. 68, no. 2, pp. 221–245, 1998. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  9. H. Kanai, H. Ogata, and M. Taniguchi, “Estimating function approach for CHARN models,” Metron, vol. 68, pp. 1–21, 2010. View at Google Scholar
  10. D. Tjøstheim, “Estimation in nonlinear time series models,” Stochastic Processes and Their Applications, vol. 21, no. 2, pp. 251–273, 1986. View at Publisher · View at Google Scholar
  11. Z. Lu and Z. Jiang, “L1 geometric ergodicity of a multivariate nonlinear AR model with an ARCH term,” Statistics & Probability Letters, vol. 51, no. 2, pp. 121–130, 2001. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  12. A. S. Kholevo, “On estimates of regression coefficients,” Theory of Probability and its Applications, vol. 14, pp. 79–104, 1969. View at Google Scholar
  13. L. Le Cam, “Locally asymptotically normal families of distributions. Certain approximations to families of distributions and their use in the theory of estimation and testing hypotheses,” vol. 3, pp. 37–98, 1960. View at Google Scholar · View at Zentralblatt MATH
  14. H. Kato, M. Taniguchi, and M. Honda, “Statistical analysis for multiplicatively modulated nonlinear autoregressive model and its applications to electrophysiological signal analysis in humans,” IEEE Transactions on Signal Processing, vol. 54, pp. 3414–3425, 2006. View at Google Scholar