Opportunities of the minimum Anderson–Darling estimator as a variant of the maximum likelihood method |
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Authors: | Mathias Raschke |
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Institution: | Stolze-Schrey-Str.1, Wiesbaden, Germany |
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Abstract: | We reveal that the minimum Anderson–Darling (MAD) estimator is a variant of the maximum likelihood method. Furthermore, it is shown that the MAD estimator offers excellent opportunities for parameter estimation if there is no explicit formulation for the distribution model. The computation time for the MAD estimator with approximated cumulative distribution function is much shorter than that of the classical maximum likelihood method with approximated probability density function. Additionally, we research the performance of the MAD estimator for the generalized Pareto distribution and demonstrate a further advantage of the MAD estimator with an issue of seismic hazard analysis. |
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Keywords: | Bernoulli distribution earthquake ground motion relation generalized Pareto distribution likelihood function minimum distance estimator minimum Anderson–Darling estimator |
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