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Binned goodness-of-fit tests based on the empirical characteristic function

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  • Meintanis, S.
  • Ushakov, N. G.

Abstract

Goodness-of-fit tests based on the empirical characteristic function are studied when data are given in prebinned form. Conditions are obtained under which the limiting distribution of a binned test statistic coincides with that of the corresponding ordinary test statistic. Using a simulation experiment, we demonstrate that binned tests do not essentially lose in power compared with ordinary tests, while at the same time are computationally less demanding.

Suggested Citation

  • Meintanis, S. & Ushakov, N. G., 2004. "Binned goodness-of-fit tests based on the empirical characteristic function," Statistics & Probability Letters, Elsevier, vol. 69(3), pages 305-314, September.
    • Handle: RePEc:eee:stapro:v:69:y:2004:i:3:p:305-314
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    References listed on IDEAS

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    1. N. Henze, 1990. "An approximation to the limit distribution of the epps-pulley test statistic for normality," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 37(1), pages 7-18, December.
    2. L. Baringhaus & N. Henze, 1988. "A consistent test for multivariate normality based on the empirical characteristic function," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 35(1), pages 339-348, December.
    3. Nora Gürtler & Norbert Henze, 2000. "Goodness-of-Fit Tests for the Cauchy Distribution Based on the Empirical Characteristic Function," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(2), pages 267-286, June.
    4. B. W. Silverman, 1982. "Kernel Density Estimation Using the Fast Fourier Transform," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(1), pages 93-99, March.
    5. Hall, Peter & Wand, M. P., 1996. "On the Accuracy of Binned Kernel Density Estimators," Journal of Multivariate Analysis, Elsevier, vol. 56(2), pages 165-184, February.
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