Integrated squared error estimation of Cauchy parameters
AbstractWe show that integrated squared error estimation of the parameters of a Cauchy distribution, based on the empirical characteristic function, is simple, robust and efficient. The k-L estimator of Koutrouvelis (Biometrika 69 (1982) 205) is more difficult to use, less robust and at best only marginally more efficient.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 55 (2001)
Issue (Month): 4 (December)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Junjiro Ogawa, 1960. "Determination of optimum spacings for the estimation of the scale parameter of an exponential distribution based on sample quantiles," Annals of the Institute of Statistical Mathematics, Springer, vol. 12(2), pages 135-141, June.
- Besbeas, Panagiotis & Morgan, Byron J. T., 2004. "Integrated squared error estimation of normal mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 44(3), pages 517-526, January.
- Meintanis, Simos G. & Iliopoulos, George, 2008. "Fourier methods for testing multivariate independence," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1884-1895, January.
- Muneya Matsui & Akimichi Takemura, 2005. "Empirical characteristic function approach to goodness-of-fit tests for the Cauchy distribution with parameters estimated by MLE or EISE," Annals of the Institute of Statistical Mathematics, Springer, vol. 57(1), pages 183-199, March.
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