adaHuber.mean {adaHuber} | R Documentation |
Adaptive Huber Mean Estimation
Description
Adaptive Huber mean estimator from a data sample, with robustification parameter \tau
determined by a tuning-free principle.
Usage
adaHuber.mean(X, epsilon = 1e-04, iteMax = 500)
Arguments
X |
An |
epsilon |
(optional) The tolerance level in the iterative estimation procedure, iteration will stop when |
iteMax |
(optional) Maximum number of iterations. Default is 500. |
Value
A list including the following terms will be returned:
mu
The Huber mean estimator.
tau
The robustness parameter determined by the tuning-free principle.
iteration
The number of iterations in the estimation procedure.
References
Huber, P. J. (1964). Robust estimation of a location parameter. Ann. Math. Statist., 35, 73–101.
Wang, L., Zheng, C., Zhou, W. and Zhou, W.-X. (2021). A new principle for tuning-free Huber regression. Stat. Sinica, 31, 2153-2177.
Examples
n = 1000
mu = 2
X = rt(n, 2) + mu
fit.mean = adaHuber.mean(X)
fit.mean$mu