In this paper we investigate the robustness properties of the class of minimum power divergence estimators for grouped data. This class contains the classical maximum likelihood estimators for grouped data. We find that the bias of these estimators due to deviations from the assumed underlying model can be large. Therefore we propose a more general class of estimators which allow us to construct robust procedures.
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Length: 27 pages Date of creation: 1996 Date of revision: Handle: RePEc:gen:geneem:96.02
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Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation