The Anderson-Darling test of fit for the power law distribution from left censored samples
AbstractMaximum likelihood estimation and a test of fit based on the Anderson-Darling statistic is presented for the case of the power law distribution when the parameters are estimated from a left-censored sample. Expressions for the maximum likelihood estimators and tables of asymptotic percentage points for the A^2 statistic are given. The technique is illustrated for data from the Dow Jones Industrial Average index, an example of high theoretical and practical importance in Econophysics, Finance, Physics, Biology and, in general, in other related Sciences such as Complexity Sciences.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1004.0417.
Date of creation: Apr 2010
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Publication status: Published in Physica A, Volume 389, Issue 17, 3508-3515 (2010)
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- Mauro Politi & Nicolas Millot & Anirban Chakraborti, 2011. "The near-extreme density of intraday log-returns," Post-Print hal-00827942, HAL.
- Politi, Mauro & Millot, Nicolas & Chakraborti, Anirban, 2012. "The near-extreme density of intraday log-returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 147-155.
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