Description Usage Arguments Value See Also Examples
Converts covariances from a parameterization by eigenvalue decomposition or cholesky factorization to representation as a 3D array.
1  decomp2sigma(d, G, scale, shape, orientation, ...)

d 
The dimension of the data. 
G 
The number of components in the mixture model. 
scale 
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 
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 
Either a d by d by G array whose 
... 
Catches unused arguments from an indirect or list call via 
A 3D array whose [,,k]
th component is the
covariance matrix of the kth component in an MVN mixture model.
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