Abstract
We assume that the distribution of a sample is the product of symmetrical distributions with unknown location and scale parameters, but the observations are actually dependent. We establish the bias-robustness of L-estimates of location against dependence. We show that the sample mean is the most robust estimate and either the sample median or the midrange is the most sensitive one. This contrasts with classical results dealing with robustness against disturbing marginal distributions.
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