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Selecting the best model to fit data

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  • Freeman, T.Graham

Abstract

The paper reviews many of the techniques used to choose the most appropriate model order when fitting a choice of models to available data. The goodness-of-fit test alone is often inadequate, since models with too many parameters can appear to fit the data better, but the improved fit does not carry over to new data on the same process.

Suggested Citation

  • Freeman, T.Graham, 1985. "Selecting the best model to fit data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 27(2), pages 137-140.
    • Handle: RePEc:eee:matcom:v:27:y:1985:i:2:p:137-140
    DOI: 10.1016/0378-4754(85)90032-1
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    References listed on IDEAS

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    1. Brenton R. Clarke, 1983. "An Algorithm for Testing Goodness of Fit of ARMA (P, Q) Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 32(3), pages 335-344, November.
    2. T. Ozaki, 1977. "On the Order Determination of Arima Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(3), pages 290-301, November.
    3. Spriet, J.A. & Herman, P., 1983. "A simulation study of structure characterization methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 25(5), pages 452-459.
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    Cited by:

    1. Salameh, F. & Picot, A. & Chabert, M. & Maussion, P., 2017. "Regression methods for improved lifespan modeling of low voltage machine insulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 200-216.

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