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Trimmed likelihood estimation of location and scale of the normal distribution. (English) Zbl 0798.62043

The authors consider trimmed likelihood estimators of location and scale of a normal distribution such that the estimators are robust. The approach employs empirical processes and differentiability of estimating functionals and is different from P. J. Huber [Am. Math. Stat. 35, 73-101 (1964; Zbl 0136.398); ibid. 43, 1041-1067 (1972; Zbl 0254.62023)] and F. R. Hampel’s [J. Am. Stat. Assoc. 69, 383-393 (1974; Zbl 0305.62031)] approaches. The estimator for location does not depend on the scale estimate and is robust against asymmetric contamination. Simulation results support their theory.

MSC:

62F35 Robustness and adaptive procedures (parametric inference)
62F10 Point estimation
62H12 Estimation in multivariate analysis
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