A Study on the Test of Homogeneity for Nonlinear Time Series Panel Data Using Bilinear Models

중선형 모형을 이용한 비선형 시계열 패널자료의 동질성검정에 대한 연구

  • Kim, Inkyu (Dept. of Computer & Information, Woosong Information College)
  • 김인규 (우송정보대학 컴퓨터정보과)
  • Received : 2014.04.29
  • Accepted : 2014.07.20
  • Published : 2014.07.28


When the number of parameters in the time series model are diverse, it is hard to forecast because of the increasing error by a parameter estimation. If the homogeneity hypothesis which was obtained from the same model about severeal data for the time series is selected, it is easy to get the predictive value better. Nonlinear time-series panel data for each parameter for each time series, since there are so many parameters that are present, and the large number of parameters according to the parameter estimation error increases the accuracy of the forecast deteriorated. Panel present in the time series of multiple independent homogeneity is satisfied by a comprehensive time series to estimate and to test of the parameters. For studying about the homogeneity test for the m independent non-linear of the time series panel data, it needs to set the model and to make the normal conditions for the model, and to derive the homogeneity test statistic. Finally, it shows to obtain the limit distribution according to ${\chi}^2$ distribution. In actual analysis,, we can examine the result for the homogeneity test about nonlinear time series panel data which are 2 groups of stock price data.


  1. Tong, H., Non-linear Time Series, Oxford University Press, Oxford, 1990.
  2. Anderson, T. W., Repeated mearsurements on autoregressive process. Journal of American Stat. Association, Vol. 73, pp. 371-378, 1978.
  3. Lee, S. D., Test of Homogeneity for a Panel of Seasonal Autoregressive Processes, Journal of Korean Statistical Society, 22, pp. 125-132, 1993.
  4. Pham, T. D. and Tran, L. T., On the first order bilinear time series model, Journal of Allied Probability, 18, 617-627, 1981.
  5. M. M. Gaber, On the Third-Order Moment Structure and Bispectral Ananysis of Some Bilinear Time Series, Journal of Time Series Analysis, Vol. 9, pp. 11-20, 2008.
  6. Abdelouahab B., Abdelhakim A., Yule-Walker type estimators in periodic bilinear models: strong consistency and asymptotic normality, Statistical Methods and Applications, Vol. 19, pp. 1-30, 2010.
  7. Iheanyi S. Iwueze, Ohakwe Johnson, Covariance analysis of the squares of the purely diagonal bilinear time series models, Brazilian Journal of Probability and Statistics, Vo. 1, 2011.
  8. Etuk E. H. and Iwok I. A., Zero-lag white noise vector bilinear autoregressive time series models, American Journal of Scientific and Industrial Research, Vol. 3, pp. 86-93, 2012.
  9. Liu, J., A note on causality and invertibility of a general bilinear time series model, Adv. Appl. Prob, 22, pp. 247-250, 1990.