rags2ridges (version 1.2)

covML: Maximum likelihood estimation of the covariance matrix

Description

Function that gives the maximum likelihood estimate of the covariance matrix.

Usage

covML(Y)

Arguments

Y

Data matrix. Variables assumed to be represented by columns.

Value

• Function returns the maximum likelihood estimate of the covariance matrix.

Details

The function gives the maximum likelihood estimate of the covariance matrix. The input matrix Y assumes that the variables are represented by the columns.

See Also

ridgeS

Examples

## Obtain some (high-dimensional) data
p = 25
n = 10
set.seed(333)
X = matrix(rnorm(n*p), nrow = n, ncol = p)
colnames(X)[1:25] = letters[1:25]

## Obtain ML estimate covariance matrix
Cx <- covML(X)