Diagonal Gaussian mixture model hierarchical fit results class

Source: R/diaggmm.R

An S4 class to represent a hierarchical fit of a diagonal gaussian mixture model, extend icl_path-class.

Slots

model

a diaggmm-class object to store the model fitted

name

generative model name

icl

icl value of the fitted model

K

number of extracted clusters over row and columns

cl

a numeric vector with row and columns cluster indexes

obs_stats

a list with the following elements:

  • counts: numeric vector of size K with number of elements in each clusters

  • regs: list of size $K$ with statistics for each clusters

path

a list of size K-1 with each part of the path described by:

  • icl1: icl value reach with this solution for alpha=1

  • logalpha: log(alpha) value were this solution is better than its parent

  • K: number of clusters

  • cl: vector of cluster indexes

  • k,l: index of the cluster that were merged at this step

  • merge_mat: lower triangular matrix of delta icl values

  • obs_stats: a list with the following elements:

    • counts: numeric vector of size K with number of elements in each clusters

    • regs: list of size $K$ with statistics for each clusters

logalpha

value of log(alpha)

ggtree

data.frame with complete merge tree for easy plotting with ggplot2

tree

numeric vector with merge tree tree[i] contains the index of i father

train_hist

data.frame with training history information (details depends on the training procedure)