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Stochastic Neural Networks With Applications to Nonlinear Time Series

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  • Lai T.L.
  • Po-Shing Wong S.

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  • Lai T.L. & Po-Shing Wong S., 2001. "Stochastic Neural Networks With Applications to Nonlinear Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 968-981, September.
  • Handle: RePEc:bes:jnlasa:v:96:y:2001:m:september:p:968-981
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    Cited by:

    1. Prado, Raquel & Molina, Francisco & Huerta, Gabriel, 2006. "Multivariate time series modeling and classification via hierarchical VAR mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1445-1462, December.
    2. Min Gan & C.L. Philip Chen & Long Chen & Chun-Yang Zhang, 2016. "Exploiting the interpretability and forecasting ability of the RBF-AR model for nonlinear time series," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(8), pages 1868-1876, June.
    3. Mayte Suarez -Farinas & Carlos E. Pedreira & Marcelo C. Medeiros, 2004. "Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1092-1107, December.
    4. Carvalho, Alexandre X. & Tanner, Martin A., 2007. "Modelling nonlinear count time series with local mixtures of Poisson autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5266-5294, July.
    5. Tze Leung Lai & Samuel Po-Shing Wong, 2007. "Combining domain knowledge and statistical models in time series analysis," Papers math/0702814, arXiv.org.

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