LcaFit-class function

Latent Class Analysis fit results class

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). class

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