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The Recursive Fitting Of Subset Varx Models

Author

Listed:
  • Jack H. W. Penm
  • Jammie H. Penm
  • R. D. Terrell

Abstract

. A vector time series model of the form A(L)y(t) + B(L)x(t) =ε(t) is known as a vector autoregressive model with exogenous variables (VARX model) and involves a regressand vector y(t) and a regressor vector x(t). This paper provides a method for the recursive fitting of subset VARX models. It suggests the use of ascending recursions in conjunction with an order selection criterion to choose an ‘optimum’ subset VARX model.

Suggested Citation

  • Jack H. W. Penm & Jammie H. Penm & R. D. Terrell, 1993. "The Recursive Fitting Of Subset Varx Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(6), pages 603-619, November.
  • Handle: RePEc:bla:jtsera:v:14:y:1993:i:6:p:603-619
    DOI: 10.1111/j.1467-9892.1993.tb00169.x
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    Cited by:

    1. Carpio, Lucio Guido Tapia, 2019. "The effects of oil price volatility on ethanol, gasoline, and sugar price forecasts," Energy, Elsevier, vol. 181(C), pages 1012-1022.
    2. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    3. H. Glendinning, Richard, 2001. "Selecting sub-set autoregressions from outlier contaminated data," Computational Statistics & Data Analysis, Elsevier, vol. 36(2), pages 179-207, April.

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