glcInitializeSplitEigen: Initialize Gaussian Latent Class via Eigendecomposition
In RPMM: Recursively Partitioned Mixture Model

Description Usage Arguments Details Value See Also

Creates a function for initializing latent class model based on Eigendecomposition

1 2	glcInitializeSplitEigen(eigendim = 1, assignmentf = function(s) (rank(s) - 0.5)/length(s))

`eigendim`	How many eigenvalues to use
`assignmentf`	assignment function for transforming eigenvector to weight

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.

A function f(x) (see Details.)

glcInitializeSplitFanny, glcInitializeSplitHClust

RPMM documentation built on May 2, 2019, 2:52 p.m.