covMLknown | R Documentation |
Function that performs maximum likelihood estimation of the covariance matrix, with various types of assumptions on its structure.
covMLknown(
Y,
covMat = NULL,
corMat = NULL,
corType = "none",
varType = "none",
nInit = 100
)
Y |
Data |
covMat |
A positive-definite covariance |
corMat |
A positive-definite correlation |
corType |
A |
varType |
A |
nInit |
An |
The function gives the maximum likelihood estimate of the covariance matrix.
The input matrix Y
assumes that the variables are represented by the
columns.
When simultaneously covMat=NULL
, corMat=NULL
,
corType="none"
and varType="none"
the covML
-function is
invoked and the regular maximum likelihood estimate of the covariance matrix
is returned.
The maximum likelihood estimate of the covariance matrix
under the specified assumptions on its structure.
Wessel N. van Wieringen, Carel F.W. Peeters <carel.peeters@wur.nl>
covML
## Obtain some data
p = 10
n = 100
set.seed(333)
X = matrix(rnorm(n*p), nrow = n, ncol = p)
colnames(X)[1:10] = letters[1:10]
## Obtain maximum likelihood estimate covariance matrix
Cx <- covMLknown(X, corType="equi", varType="common")
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