Abstract
The moment process is appropriate for analysing random variables with a bounded support. In this paper we first briefly discuss the properties of the empirical counterpart of this process. Then the empirical moment process is utilized in a goodness-of-fit test for a three-parameter version of the standard two-sided power distribution. The procedure is applied not to the original data, but to suitably transformed data incorporating parameter estimates. Consistency of the tests is investigated under general assumptions, and the finite-sample behavior of the proposed method is investigated via a parametric bootstrap procedure.
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Meintanis, S.G., Iliopoulos, G. The Empirical Moment Process in Testing for the Generalized Two-Sided Power Distribution. J Stat Theory Pract 3, 577–586 (2009). https://doi.org/10.1080/15598608.2009.10411948
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DOI: https://doi.org/10.1080/15598608.2009.10411948