glcInitializeSplitEigen {RPMM} | R Documentation |
Initialize Gaussian Latent Class via Eigendecomposition
Description
Creates a function for initializing latent class model based on Eigendecomposition
Usage
glcInitializeSplitEigen(eigendim = 1,
assignmentf = function(s) (rank(s) - 0.5)/length(s))
Arguments
eigendim |
How many eigenvalues to use |
assignmentf |
assignment function for transforming eigenvector to weight |
Details
Creates a function f(x)
that will take a data matrix x
and
initialize a weight matrix for a two-class latent class model.
Here, the initialized classes will be based on eigendecomposition of the variance of x
.
See glcTree
for example of using “glcInitializeSplit...” to create starting values.
Value
A function f(x)
(see Details.)
See Also
glcInitializeSplitFanny
,
glcInitializeSplitHClust
[Package RPMM version 1.25 Index]