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The Statistical Analysis Of Perturbed Limit Cycle Processes Using Nonlinear Time Series Models

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  • T. Ozaki

Abstract

. Statistical analysis of perturbed limit cycle process is discussed. Limit cycles of van der Pol equation type are considered and statistical time series models for the perturbed limit cycle processes are presented. It is shown that the model shares some interesting qualitative properties although the presented models are different, in appearance, from the van der Pol equation. Applications of the model to the statistical analysis of Canadian Lynx data are also discussed with numerical results.

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  • T. Ozaki, 1982. "The Statistical Analysis Of Perturbed Limit Cycle Processes Using Nonlinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(1), pages 29-41, January.
    • Handle: RePEc:bla:jtsera:v:3:y:1982:i:1:p:29-41
    DOI: 10.1111/j.1467-9892.1982.tb00328.x
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    Cited by:

    1. Baragona, R. & Battaglia, F. & Cucina, D., 2004. "Fitting piecewise linear threshold autoregressive models by means of genetic algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 277-295, September.
    2. Chen, Song Xi & Lei, Lihua & Tu, Yundong, 2014. "Functional Coefficient Moving Average Model with Applications to forecasting Chinese CPI," MPRA Paper 67074, University Library of Munich, Germany, revised 2015.
    3. Kaboudan, M. A., 2001. "Genetically evolved models and normality of their fitted residuals," Journal of Economic Dynamics and Control, Elsevier, vol. 25(11), pages 1719-1749, November.
    4. Lai, Dejian, 1996. "Comparison study of AR models of the Canadian lynx data: A close look at BDS statistic," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 409-423, August.
    5. Gerard A. Pfann, 1991. "Employment and business cycle asymmetries: a data based study," Discussion Paper / Institute for Empirical Macroeconomics 39, Federal Reserve Bank of Minneapolis.
    6. Pfann, Gerard A., 2001. "Measuring and forecasting asymmetries in employment cycles with US labor market applications," International Journal of Forecasting, Elsevier, vol. 17(3), pages 433-445.

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