Minimum divergence estimators based on grouped data

DOI10.1023/A:1012466605316zbMath1027.62011OpenAlexW1531677953MaRDI QIDQ5949371

M. Luisa Menendez, Igor Vajda, Leandro Pardo, Domingo Morales

Publication date: 21 November 2001

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1012466605316

zbMATH Keywords

optimizationasymptotic normalityefficiencyFisher informationminimum divergence estimatorsrandom quantization

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Point estimation (62F10)

Related Items (9)

Consistency of minimum divergence estimators based on grouped data ⋮ Ordinary and penalized minimum power-divergence estimators in two-way contingency tables ⋮ A class of asymptotically efficient estimators based on sample spacings ⋮ Preliminary Phi-divergence test estimator for multinomial probabilities ⋮ Alternatives to maximum likelihood estimation based on spacings and the Kullback-Leibler divergence ⋮ Minimum disparity estimators for discrete and continuous models. ⋮ A refined Jensen's inequality in Hilbert spaces and empirical approximations ⋮ Some Universal Insights on Divergences for Statistics, Machine Learning and Artificial Intelligence ⋮ On Efficient Estimation in Continuous Models Based on Finitely Quantized Observations

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