This mode estimator is based on a gradient-like recursive algorithm. It includes the Mizoguchi-Shimura (1976) mode estimator, based on the window training procedure.
The skewness.default function from package fBasics is completed in order to implement Bickel's measure of skewness, based on the mode of the distribution considered.
naive
(Package: modeest) :
The Chernoff Mode Estimator
This estimator, also called the *naive* mode estimator, is defined as the center of the interval of given length containing the most observations. It is identical to Parzen's kernel mode estimator, when the kernel is chosen to be the uniform kernel.
This package intends to provide estimators of the mode of univariate unimodal (and sometimes multimodal) data and values of the modes of usual probability distributions.
mlv is a generic function which enables to compute an estimate of the mode of a univariate distribution. Many different estimates (or methods) are provided:
This function computes the Robertson-Cryer mode estimator described in Robertson and Cryer (1974), also called half sample mode (if bw = 1/2) or fraction sample mode (for some other bw) by Bickel (2006).
providing 
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