Sensitivity of the Chi-Squared Goodness-of-Fit Test to the Partitioning of Data
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.
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- Wallis, Kenneth F., 2001.
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Working Paper Series
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- repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
- Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2004. "Decompositions of Pearson's chi-squared test," Journal of Econometrics, Elsevier, vol. 123(1), pages 189-193, November.
- Marrocu, Emanuela & Gianna Boero, 2003. "The Performance of SETAR models by Regime: A Conditional Evaluation of Interval and Density Forecasts," Royal Economic Society Annual Conference 2003 147, Royal Economic Society.
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