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Prediction techniques for Box-Cox regression models

Author

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  • Sean Collins

Abstract

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Suggested Citation

  • Sean Collins, 1991. "Prediction techniques for Box-Cox regression models," Finance and Economics Discussion Series 148, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:148
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    Citations

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    Cited by:

    1. Proietti, Tommaso & Lütkepohl, Helmut, 2013. "Does the Box–Cox transformation help in forecasting macroeconomic time series?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 88-99.
    2. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2005. "Bootstrap prediction intervals for power-transformed time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 219-235.
    3. Selby, Brent & Kockelman, Kara M., 2013. "Spatial prediction of traffic levels in unmeasured locations: applications of universal kriging and geographically weighted regression," Journal of Transport Geography, Elsevier, vol. 29(C), pages 24-32.
    4. Franses, Philip Hans & Koop, Gary, 1998. "On the sensitivity of unit root inference to nonlinear data transformations," Economics Letters, Elsevier, vol. 59(1), pages 7-15, April.
    5. Yuanhua Feng & Wolfgang Karl Härdle, 2021. "Uni- and multivariate extensions of the sinh-arcsinh normal distribution applied to distributional regression," Working Papers CIE 142, Paderborn University, CIE Center for International Economics.

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    Keywords

    Econometric models;

    Statistics

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