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 dist_sc function.


The agglomeration method to be used in the hclust function. Default is "average", for alternatives see hclust.


Further arguments to be passed to the method hclust.


An object of class hclust is returned, which describes the tree produced by the clustering process. See for more details hclust. Additionally, the cophenetic correlation coefficient and the Gower distance are printed in the console as guidance for selecting the best agglomeration method.

See also


Other score-based IND performance functions: dist_sc_group(), dist_sc(), expect_resp(), plot_clust_sc(), plot_spiechart(), scoring(), summary_sc()


# 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")
#> With the selected agglomeration method (complete), the cophonetic correlation coeffient is 0.852 and the Gower distance is 481.34.