This test is an alternative to Pearson's X^2 goodness-of-fit test. In contrast to Pearson's X^2, no ad hoc cell collapsing is needed to avoid an inflated false positive rate in situations of sparse cell frequences. The statistic rapidly converges to the Monte-Carlo estimate as the number of draws increases.
The P value indicating whether the two tables come from the same distribution. For example, a significant result (P < alpha level) rejects the hypothesis that the two matrices are from the same distribution.
Perkins, W., Tygert, M., & Ward, R. (2011). Computing the confidence levels for a root-mean-square test of goodness-of-fit. Applied Mathematics and Computations, 217(22), 9072-9084.
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