Binned goodness-of-fit tests based on the empirical characteristic function
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.
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Volume (Year): 69 (2004)
Issue (Month): 3 (September)
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References listed on IDEAS
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- 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.
- L. Baringhaus & N. Henze, 1988. "A consistent test for multivariate normality based on the empirical characteristic function," Metrika, Springer, vol. 35(1), pages 339-348, December.
- 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, vol. 52(2), pages 267-286, June.
- N. Henze, 1990. "An approximation to the limit distribution of the epps-pulley test statistic for normality," Metrika, Springer, vol. 37(1), pages 7-18, December.
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