Man pages for dbrobust
Robust Distance-Based Visualization and Analysis of Mixed-Type Data
| calculate_distances | Compute Distance or Similarity Matrices |
| convert_to_dist | Convert a similarity or distance matrix to a 'dist' object |
| Data_HC_contamination | High-correlation dataset with contamination |
| Data_HC_no_contamination | High-correlation dataset without contamination |
| Data_MC_contamination | Moderate-correlation dataset with contamination |
| Data_MC_no_contamination | Moderate-correlation dataset without contamination |
| dist_binary | Compute pairwise binary distances |
| dist_categorical | Compute pairwise distances for categorical data |
| dist_continuous | Compute pairwise distances for continuous numeric data |
| dist_mixed | Compute Gower dissimilarity for mixed-type data |
| format_output | Format distance or similarity matrix output |
| get_custom_palette | Generate a Custom Color Palette |
| make_euclidean | Force a Pairwise Squared Distance Matrix to Euclidean Form |
| plot_heatmap | Visualize a Distance or Similarity Matrix as a Heatmap with... |
| plot_mds | Plot MDS Results with Grouped Scatter and Density Plots... |
| plot_qgraph | Plot a Network Graph from a Distance Matrix |
| robust_covariance_gv | Robust Covariance Estimation Based on Geometric Variability |
| robust_distances | Compute Robust Squared Distances for Mixed Data |
| robust_ggower | Compute Robust Generalized Gower Distance |
| robust_RelMS | Robust RelMS Distance |
| visualize_distances | Visualize Distance Matrices via MDS, Heatmap, or Network... |
