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Tail fit and the Zipf–Pareto law
Authors:Paul Schuette  Marcus C. Spruill
Affiliation:(1) Department of Mathematics and Computer Sciences, Meredith College, 3800 Hillsborough Street, Raleigh, NC 27607-5298, USA;(2) School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332-0160, USA
Abstract:A limit theorem with bounds on the rate of convergence is proven. The joint distribution of a fixed number of relative decrements of the top order statistics from a random sample converges to the limit as the sample size increases if and only if the underlying distribution is in essence a Pareto. In conjunction with a chi-square test of fit, it provides an asymptotically distribution-free test of fit to the family of distributions with regularly varying tails at infinity. When the limit distribution holds, rank-size plots obey Zipf’s law. The test can be used to detect departures from this Zipf–Pareto law.
Keywords:von Mises condition  Regularly varying tail  Asymptotic distribution  Rate of convergence  Chi-square fit  Hill’  s estimator  Exponential distribution  Order statistics
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