Sensitivity of the Chi-Squared Goodness-of-Fit Test to the Partitioning of Data

Gianna Boero (), Jeremy Smith and Kenneth Wallis ()

The Warwick Economics Research Paper Series (TWERPS) from University of Warwick, Department of Economics

Abstract: In this paper we conduct a Monte Carlo study to determine the power of Pearson’s overall goodness-of-fit test as well as the “Pearson analog” tests (see Anderson (1994)) to detect rejections due to shifts in variance, skewness and kurtosis, as we vary the number and location of the partition points. Simulations are conducted for small and moderate sample sizes. While it is generally recommended that to improve the power of the goodness-of-fit test the partition points are equiprobable, we find that power can be improved by the use of non-equiprobable partitions.

Keywords: Pearson’s Goodness-of-fit test; Distributional assumptions; Monte Carlo; Normality; partitions (search for similar items in EconPapers)
JEL-codes: C1 C12 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://warwick.ac.uk/fac/soc/economics/research/workingpapers/2008/twerp694.pdf

Related works:
Journal Article: The Sensitivity of Chi-Squared Goodness-of-Fit Tests to the Partitioning of Data (2005)
Working Paper: Sensitivity of the chi-squared goodness-of-fit test to the partitioning of data (2004)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wrk:warwec:694

Access Statistics for this paper

More papers in The Warwick Economics Research Paper Series (TWERPS) from University of Warwick, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Margaret Nash ().