Maximum likelihood estimation of the covariance matrix
Function that gives the maximum likelihood estimate of the covariance matrix.
covML(Y, cor = FALSE)
Y |
Data |
cor |
A |
The function gives the maximum likelihood (ML) estimate of the covariance
matrix. The input matrix Y assumes that the variables are represented
by the columns. Note that when the input data is standardized, the ML
covariance matrix of the scaled data is computed. If a correlation matrix is
desired, use cor = TRUE.
Function returns the maximum likelihood estimate of the covariance
matrix. In case cor = TRUE, the correlation matrix is
returned.
Carel F.W. Peeters <cf.peeters@vumc.nl>, Wessel N. van Wieringen
## 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) ## Obtain correlation matrix Cx <- covML(X, cor = TRUE)
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