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== Limitations ==
As with any regression procedure, a high degree of association between predictor variables can sometimes cause the individual transformation estimates to be highly variable, even though the complete model is reasonably stable. When this is suspected, running the algorithm on randomly selected subsets of the data, or on [[Bootstrapping (statistics)|bootstrap samples]] can assist in assessing the variability.
ACE has shown some sensitivity to the order of the predictor variables and extreme outliers.<ref>De Veaux, R. 1990. Finding Transformations for Regression Using the ACE Algorithm. Sociological Methods and Research 18(2-3) 327-359.</ref> Long tailed distributions can lead to the above mentioned instability.
In real world applications one can never be sure that all relevant variables are observed and ACE will always recommend a transform. Thus the recommended transforms can be symptoms of this problem rather than what ACE is trying to solve.<ref>Pregibon, D., Vardi, Y. 1985. Estimating Optimal Transformations for Multiple Regression and Correlation: Comment. Journal of the American Statistical Association. 80(391) 598-601</ref>
== References ==
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