Initialize Gaussian Latent Class via Eigendecomposition

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Description

Creates a function for initializing latent class model based on Eigendecomposition

Usage

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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

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