DcLbmPath-class function

Degree corrected Latent Block Model hierarchical fit results class

An S4 class to represent a fit of a degree corrected stochastic block model for co_clustering, extend IclPath-class. class

Slots

• model: a DcLbm-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

• Krow: number of extracted row clusters

• Kcol: number of extracted column clusters

• 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
    * din: numeric vector of size K which store the sums of in-degrees for each clusters
    * dout: numeric vector of size K which store the sums of out-degrees for each clusters
    * x_counts: matrix of size K*K with the number of links between each pair of clusters
    * co_x_counts: matrix of size Krow*Kcol with the number of links between each pair of row and column cluster
  

• clrow: a numeric vector with row cluster indexes

• clcol: a numeric vector with column cluster indexes

• Nrow: number of rows

• Ncol: number of columns

• 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 elements:
      
       * counts: numeric vector of size K with number of elements in each clusters
       * din: numeric vector of size K which store the sums of in-degrees for each clusters
       * dout: numeric vector of size K which store the sums of out-degrees for each clusters
       * x_counts: matrix of size K*K with the number of links between each pair of clusters
       * co_x_counts: matrix of size Krow*Kcol with the number of links between each pair of row and column cluster
  

• 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

• ggtreerow: data.frame with complete merge tree of row clusters for easy plotting with ggplot2

• ggtreecol: data.frame with complete merge tree of column clusters for easy plotting with ggplot2

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

See Also

plot,DcLbmPath,missing-method