Interest in transform methods for normalizing test statistics declined with the advent of computers. More recently, small sample asymptotic methods have been developed to approximate the distributions of complicated test statistics. We here propose a generalization to a similar range of statistics of a classical symmetrizing transform. It is shown to behave in a parametric neighborhood similarly to methods that exploit exponential tilting. It shows promise for application to a wide range of inference problems.
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