Publication:
Estimators based on sample quantiles using (h,phi)-entropy measures

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1998-07
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Pergamon-Elsevier Science Ltd
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A point estimation procedure based on the maximum entropy principle for (h, phi) entropies is proposed using sample quantiles. These estimators are efficient and asymptotically normal under standard regularity conditions. A test for goodness-of-fit is constructed, being the corresponding statistic asymptotically distributed chi-squared. These results generalize the results obtained in [1].
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M.L. Menéndez, D. Morales and L. Pardo, Maximum entropy principle and statistical inference on condensed ordered data, Statistics and Probability Letters (to appear). E. Bofinger, Goodness of fit using sample quantiles, Journal of the Royal Statistical Society, Series B 35, 277-284, (1973). T.R.C. Read and N.A.C. Cressie, Goodness of Fit Statistics for Discrete Multivariate Data, Springer-Verlag, (1988). A. Rényi, On measures of entropy and information, In Proc. 4 th Berkeley Syrup. Math. Statist. and Prob., Volume 1, pp. 547-561, (1961). J. Havrda and F. Charvat, Quantification of classification processes. Concept of structural a-entropy, Kybernetika 2, 30-55, (1967). S. Arimoto, Information theoretical considerations on estimation problems, Information and Control 19, 181-194, (1971). B.D. Sharma and D.P. Mittal, New nonadditive measures of entropy for discrete probability distributions, J. Math. Sci. i0, 28-40, (1977). M. Salicrú, M.L. Menéndez, D. Morales and L. Pardo, Asymptotic distribution of (h, ¢) entropies, Communications in Statitstics; Theory and Methods 22 (7), 2015-2031, (1993). L. Pardo, D. Morales, M. Salicrú and M.L. Menéndez, Large sample behavior of entropy measures when parameters are estimated, Communications in Statitstics; Theory and Methods 26 (2), 483-501, (1997). M.L. Menéndez, D. Morales, L. Pardo and M. Salicrú, (h, ¢)-entropy differential metric, Applications of Mathematics 42 (2), 81-98, (1997).
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