huber.cov {FarmTest} | R Documentation |
Tuning-free Huber-type covariance estimation
Description
The function calculates adaptive Huber-type covariance estimator from a data sample, with robustification parameter \tau
determined by a tuning-free principle.
For the input matrix X
, both low-dimension (p < n
) and high-dimension (p > n
) are allowed.
Usage
huber.cov(X)
Arguments
X |
An |
Value
A p
by p
Huber-type covariance matrix estimator will be returned.
References
Huber, P. J. (1964). Robust estimation of a location parameter. Ann. Math. Statist., 35, 73–101.
Ke, Y., Minsker, S., Ren, Z., Sun, Q. and Zhou, W.-X. (2019). User-friendly covariance estimation for heavy-tailed distributions. Statis. Sci., 34, 454-471.
See Also
huber.mean
for tuning-free Huber mean estimation and huber.reg
for tuning-free Huber regression.
Examples
n = 100
d = 50
X = matrix(rt(n * d, df = 3), n, d) / sqrt(3)
Sigma = huber.cov(X)
[Package FarmTest version 2.2.0 Index]