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Minimum Divergence Estimators Based on Grouped Data


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  • M. Menéndez
  • D. Morales
  • L. Pardo
  • I. Vajda
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    Bibliographic Info

    Article provided by Springer in its journal Annals of the Institute of Statistical Mathematics.

    Volume (Year): 53 (2001)
    Issue (Month): 2 (June)
    Pages: 277-288

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    Handle: RePEc:spr:aistmt:v:53:y:2001:i:2:p:277-288

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    Keywords: Minimum divergence estimators; random quantization; asymptotic normality; efficiency; Fisher information; optimization;


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    1. Menéndez, M. & Morales, D. & Pardo, L., 1997. "Maximum entropy principle and statistical inference on condensed ordered data," Statistics & Probability Letters, Elsevier, vol. 34(1), pages 85-93, May.
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    Cited by:
    1. Samantha Leorato, 2008. "A refined Jensen’s inequality in Hilbert spaces and empirical approximations," CEIS Research Paper 134, Tor Vergata University, CEIS, revised 24 Nov 2008.
    2. Gupta, A.K. & Nguyen, T. & Pardo, L., 2006. "Preliminary Phi-divergence test estimator for multinomial probabilities," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1749-1773, April.
    3. Aylin Alin & Serdar Kurt, 2008. "Ordinary and penalized minimum power-divergence estimators in two-way contingency tables," Computational Statistics, Springer, vol. 23(3), pages 455-468, July.
    4. Bassetti, Federico & Bodini, Antonella & Regazzini, Eugenio, 2007. "Consistency of minimum divergence estimators based on grouped data," Statistics & Probability Letters, Elsevier, vol. 77(10), pages 937-941, June.
    5. Federico Bassetti & Eugenio Regazzini, 2005. "Asymptotic distribution and robustness of minimum total variation distance estimators," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 55-80.


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