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Robust Box-Cox transformations based on minimum residual autocorrelation

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  • Marazzi, Alfio
  • Yohai, Victor J.

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  • Marazzi, Alfio & Yohai, Victor J., 2006. "Robust Box-Cox transformations based on minimum residual autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2752-2768, June.
    • Handle: RePEc:eee:csdana:v:50:y:2006:i:10:p:2752-2768
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    References listed on IDEAS

    as
    1. Cheng, Tsung-Chi, 2005. "Robust regression diagnostics with data transformations," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 875-891, June.
    2. Hössjer, Ola, 1992. "On the optimality of S-estimators," Statistics & Probability Letters, Elsevier, vol. 14(5), pages 413-419, July.
    3. Han, Aaron K., 1987. "A non-parametric analysis of transformations," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 191-209, July.
    4. Foster A. M. & Tian L. & Wei L. J., 2001. "Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1097-1101, September.
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    Cited by:

    1. Luke A. Prendergast & Simon J. Sheather, 2013. "On Sensitivity of Inverse Response Plot Estimation and the Benefits of a Robust Estimation Approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(2), pages 219-237, June.
    2. Gianna S. Monti & Peter Filzmoser & Roland C. Deutsch, 2018. "A Robust Approach to Risk Assessment Based on Species Sensitivity Distributions," Risk Analysis, John Wiley & Sons, vol. 38(10), pages 2073-2086, October.

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