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Weighted quantile-based estimation for a class of transformation distributions

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  • Rayner, G. D.
  • MacGillivray, H. L.

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  • Rayner, G. D. & MacGillivray, H. L., 2002. "Weighted quantile-based estimation for a class of transformation distributions," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 401-433, June.
    • Handle: RePEc:eee:csdana:v:39:y:2002:i:4:p:401-433
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    References listed on IDEAS

    as
    1. Collins, Daniel W & Ledolter, Johannes & Rayburn, Judy Dawson, 1987. "Some Further Evidence on the Stochastic Properties of Systematic Risk," The Journal of Business, University of Chicago Press, vol. 60(3), pages 425-448, July.
    2. W. R. van Zwet, 1964. "Convex transformations: A new approach to slcewness and kurtosis," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 18(4), pages 433-441, December.
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    Cited by:

    1. Xu, Ganggang & Genton, Marc G., 2015. "Efficient maximum approximated likelihood inference for Tukey’s g-and-h distribution," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 78-91.
    2. Fischer, Matthias J., 2004. "The L-distribution and skew generalizations," Discussion Papers 63/2004, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    3. Xu, Yihuan & Iglewicz, Boris & Chervoneva, Inna, 2014. "Robust estimation of the parameters of g-and-h distributions, with applications to outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 66-80.
    4. Fischer, Matthias J., 2006. "The L-distribution and skew generalizations," Discussion Papers 75/2006, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    5. Ong, Victor M.-H. & Nott, David J. & Tran, Minh-Ngoc & Sisson, Scott A. & Drovandi, Christopher C., 2018. "Likelihood-free inference in high dimensions with synthetic likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 271-291.
    6. Li, J. & Nott, D.J. & Fan, Y. & Sisson, S.A., 2017. "Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 77-89.

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