We consider a robust parameter estimator minimizing an empirical approximation to the q-entropy and show its relationship to minimization of power divergences through a simple parameter transformation. The estimator balances robustness and efficiency through a tuning constant q and avoids kernel density smoothing. We derive an upper bound to the estimator mean squared error under a contaminated reference model and use it as a min-max criterion for selecting q.
On robust estimation via pseudo-additive information / Ferrari, Davide; D., La Vecchia. - In: BIOMETRIKA. - ISSN 0006-3444. - ELETTRONICO. - 99:1(2011), pp. 238-244. [10.1093/biomet/asr061]
On robust estimation via pseudo-additive information
FERRARI, Davide;
2011
Abstract
We consider a robust parameter estimator minimizing an empirical approximation to the q-entropy and show its relationship to minimization of power divergences through a simple parameter transformation. The estimator balances robustness and efficiency through a tuning constant q and avoids kernel density smoothing. We derive an upper bound to the estimator mean squared error under a contaminated reference model and use it as a min-max criterion for selecting q.
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