Robust Estimators of the Mode and Skewness of Continuous Data

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Robust and efficient estimation of the mode of continuous data: the mode as a viable measure of central tendency (2003, methodology): “The midpoint of the shortest half sample (location of the least median of squares) and the mean of the shortest half sample (Rousseeuw and Leroy, 1987) are highly biased estimators of the mode (Bickel, 2001a). A low-bias mode estimator, the half-sample mode (HSM), can be computed by repeatedly takin”
Properties and Estimation of Asymmetric Exponential Power Distribution (2007, methodology): “When location parameter 0 can be consistently estimated by a nonparametric method (see Andrews et al. (1972) and Bickel (2002)), the MLEs of other parameters are still consistent, asymptotically normal but may not be e¢ cient.”
Volatility Modeling with a Generalized t Distribution (2017, unknown): “The ML estimators of these parameters are consistent and asymptotically normal when is estimated by the mode, but they may not be efficient; see Bickel (2002).”