LcaFit-class: Latent Class Analysis fit results class

In comeetie/greed: Clustering and Model Selection with the Integrated Classification Likelihood

Latent Class Analysis fit results class

Description

An S4 class to represent a fit of a Latent Class Analysis model for categorical data clustering, extend IclFit-class. The original data must be an n x p matrix where p is the number of variables and each variable is encoded as a factor (integer-valued).

Slots

model

a Lca-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 cluster indexes

obs_stats

a list with the following elements:

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

• x_counts: matrix of size K*D with the number of occurrences of each modality for each clusters

move_mat

binary matrix which store move constraints

train_hist

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

See Also

coef,LcaFit-method

comeetie/greed documentation built on Oct. 10, 2022, 5:37 p.m.