clust_sc computes a hierarchical cluster analysis for the identification
of indicator redundancies.
clust_sc(dist_mat, method_clust = "average", ...)
The distance matrix computed by the
The agglomeration method to be used in the
Further arguments to be passed to the method
An object of class
hclust is returned, which describes the tree produced by the
clustering process. See for more details
the cophenetic correlation coefficient and the Gower distance are printed in the
console as guidance for selecting the best agglomeration method.
# Using the Baltic Sea demo data scores_tbl <- scoring(trend_tbl = model_trend_ex, mod_tbl = all_results_ex, press_type = press_type_ex) scores_mat <- summary_sc(scores_tbl)$scores_matrix dist_matrix <- dist_sc(scores_mat, method_dist = "euclidean") clust_analysis <- clust_sc(dist_matrix, method_clust = "complete")#>