cov_ML: Maximum likelihood estimator of mean vector and covariance...

In robmed: (Robust) Mediation Analysis

Maximum likelihood estimator of mean vector and covariance matrix

Description

Compute the maximum likelihood estimator of the mean vector and the covariance matrix.

Usage

cov_ML(x, ...)

Arguments

x	a numeric matrix or data frame.
...	additional arguments are currently ignored.

Value

An object of class "cov_ML" with the following components:

center	a numeric vector containing the mean vector estimate.
cov	a numeric matrix containing the covariance matrix estimate.
n	an integer giving the number of observations.

Author(s)

Andreas Alfons

References

Zu, J. and Yuan, K.-H. (2010) Local Influence and Robust Procedures for Mediation Analysis. Multivariate Behavioral Research, 45(1), 1–44. doi:10.1080/00273170903504695.

See Also

test_mediation(), fit_mediation()

Examples

data("BSG2014")

# define variables
x <- "ValueDiversity"
y <- "TeamCommitment"
m <- "TaskConflict"

# compute Huber M-estimator
cov_ML(BSG2014[, c(x, y, m)])

robmed documentation built on July 9, 2023, 6:29 p.m.