Description Usage Arguments Details
Specification of variance parameters for the various types of Gaussian mixture models.
1  mclustVariance(modelName, d = NULL, G = 2)

modelName 
A character string specifying the model. 
d 
A integer specifying the dimension of the data. 
G 
An integer specifying the number of components in the mixture model. 
The variance
component in the parameters list from the
output to e.g. me
or mstep
or input to e.g. estep
may contain one or more of the following arguments, depending on the model:
modelName
A character string indicating the model.
d
The dimension of the data.
G
The number of components in the mixture model.
sigmasq
for the onedimensional models ("E"
, "V"
) and spherical
models ("EII"
, "VII"
). This is either a vector whose
kth component is the variance for the kth component in
the mixture model ("V"
and "VII"
), or a scalar giving
the common variance for all components in the mixture model ("E"
and "EII"
).
Sigma
For the equal variance models "EII"
, "EEI"
, and
"EEE"
.
A d by d matrix giving the common covariance for all
components of the mixture model.
cholSigma
For the equal variance model "EEE". A d by d upper triangular matrix giving the Cholesky factor of the common covariance for all components of the mixture model.
sigma
For all multidimensional mixture models. A
d by d by G matrix array whose
[,,k]
th entry is the covariance matrix for
the kth component of the mixture model.
cholsigma
For the unconstrained covariance mixture model "VVV"
.
A d by d by G matrix array whose
[,,k]
th entry is the upper triangular Cholesky factor
of the covariance matrix for the kth component of the
mixture model.
scale
For diagonal models "EEI"
, "EVI"
, "VEI"
,
"VVI"
and constantshape models "EEV"
and "VEV"
.
Either a Gvector giving the scale of the covariance (the
dth root of its determinant) for each component in the
mixture model, or a single numeric value if the scale is the
same for each component.
shape
For diagonal models "EEI"
, "EVI"
, "VEI"
,
"VVI"
and constantshape models "EEV"
and "VEV"
.
Either a G by d matrix in which the kth
column is the shape of the covariance matrix (normalized to have
determinant 1) for the kth component, or a
dvector giving a common shape for all components.
orientation
For the constantshape models "EEV"
and "VEV"
.
Either a d by d by G array whose
[,,k]
th entry is the orthonomal matrix whose
columns are the eigenvectors of the covariance matrix of
the kth component, or a d by d
orthonormal matrix if the mixture components have a
common orientation. The orientation
component
is not needed in spherical and diagonal models, since
the principal components are parallel to the coordinate axes
so that the orientation matrix is the identity.
In all cases, the value
1
is used as a placeholder for unknown nonzero entries.
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