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Consistency of minimum divergence estimators based on grouped data

Author

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  • Bassetti, Federico
  • Bodini, Antonella
  • Regazzini, Eugenio

Abstract

Consistency of minimum divergence estimators, based on grouped data, is studied under conditions which, to our knowledge, are weaker than the ones considered in the existing literature. Comments on the hypotheses and the interpretation of the main results are made, and an illustrative example is given.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:stapro:v:77:y:2007:i:10:p:937-941
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    References listed on IDEAS

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    1. 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.
    2. M. Menéndez & D. Morales & L. Pardo & I. Vajda, 2001. "Minimum Divergence Estimators Based on Grouped Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(2), pages 277-288, June.
    3. 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. Emanuele Dolera, 2022. "Preface to the Special Issue on “Bayesian Predictive Inference and Related Asymptotics—Festschrift for Eugenio Regazzini’s 75th Birthday”," Mathematics, MDPI, vol. 10(15), pages 1-4, July.

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