robmed (version 0.4.0)

cov_ML: 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.

References

Zu, J. and Yuan, K.-H. (2010) Local influence and robust procedures for mediation analysis. Multivariate Behavioral Research, 45(1), 1--44.

See Also

test_mediation, fit_mediation

Examples

# NOT RUN {
data("BSG2014")

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

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

# }