Binned goodness-of-fit tests based on the empirical characteristic function
AbstractGoodness-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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 69 (2004)
Issue (Month): 3 (September)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.