Approximation of distributions by using the Anderson Darling statistic

Eckhard Liebscher

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 22, 6732-6745

Abstract: In practice, it is often not possible to find an appropriate family of distributions which can be used for fitting the sample distribution with high precision. In these cases, it seems to be opportune to search for the best approximation by a family of distributions instead of an exact fit. In this paper, we consider the Anderson–Darling statistic with plugged-in minimum distance estimator for the parameter vector. We prove asymptotic normality of the Anderson–Darling statistic which is used for a test of goodness of approximation. Moreover, we introduce a measure of discrepancy between the sample distribution and the model class.

Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/03610926.2014.966844

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