Goodness of Fit: an axiomatic approach
An axiomatic approach is used to develop a one-parameter family of measures of divergence between distributions. These measures can be used to perform goodness-of-fit tests with good statistical properties. Asymptotic theory shows that the test statistics have well-defined limiting distributions which are however analytically intractable. A parametric bootstrap procedure is proposed for implementation of the tests. The procedure is shown to work very well in a set of simulation experiments, and to compare favourably with other commonly used goodness-of-fit tests. By varying the parameter of the statistic, one can obtain information on how the distribution that generated a sample diverges from the target family of distributions when the true distribution does not belong to that family. An empirical application analyses a UK income data set.
|Date of creation:||08 Nov 2011|
|Date of revision:|
|Note:||View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00639075/en/|
|Contact details of provider:|| Web page: http://hal.archives-ouvertes.fr/|
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.:
- repec:cup:cbooks:9780521589826 is not listed on IDEAS
- repec:cup:cbooks:9780521589819 is not listed on IDEAS
- repec:cup:cbooks:9780521589833 is not listed on IDEAS
- Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, EconWPA, revised 05 Mar 1996.
When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:halshs-00639075. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD)
If references are entirely missing, you can add them using this form.