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Interval prediction for chaotic time series

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  • Silvano Bordignon
  • Francesco Lisi

Abstract

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Suggested Citation

  • Silvano Bordignon & Francesco Lisi, 2001. "Interval prediction for chaotic time series," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 117-140.
  • Handle: RePEc:mtn:ancoec:2001:3:09
    as

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    File URL: https://www.dss.uniroma1.it/RePec/mtn/articoli/2001-LIX-3_4-9.pdf
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    References listed on IDEAS

    as
    1. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, "undated". "Evaluating Density Forecasts," CARESS Working Papres 97-18, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
    2. Bordignon, Silvano & Lisi, Francesco, 2001. "Predictive accuracy for chaotic economic models," Economics Letters, Elsevier, vol. 70(1), pages 51-58, January.
    3. Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
    4. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
    5. Yao, Qiwei & Tong, Howell, 1994. "Quantifying the influence of initial values on nonlinear prediction," LSE Research Online Documents on Economics 19426, London School of Economics and Political Science, LSE Library.
    6. Gooijer, Jan G. De & Gannoun, Ali, 2000. "Nonparametric conditional predictive regions for time series," Computational Statistics & Data Analysis, Elsevier, vol. 33(3), pages 259-275, May.
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