serial: Annals of the Institute of Statistical Mathematics vol.53, 2 (2001), p. 277-288
project(s): GA102/99/1137, GA ČR
keywords: minimum divergence estimators, random quantization, asymptotic normality
It is shown that an optimal grouping of data (quantification) leads to a negligible inefficiency in continuous parametric models. Robust estimators achieving the negligible inefficiency are introduced and their asymptotic theory is established.