clusterSim

Distance measures (GDM1, GDM2, Sokal-Michener, Bray-Curtis, for symbolic interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap, Davies-Bouldin), data normalization formulas (metric data, interval-valued symbolic data), data generation (typical and non-typical data), HINoV method, replication analysis, linear ordering methods, spectral clustering, agreement indices between two partitions, plot functions (for categorical and symbolic interval-valued data). (MILLIGAN, G.W., COOPER, M.C. (1985) doi:10.1007/BF02294245, HUBERT, L., ARABIE, P. (1985) doi:10.1007%2FBF01908075, RAND, W.M. (1971) doi:10.1080/01621459.1971.10482356, JAJUGA, K., WALESIAK, M. (2000) doi:10.1007/978-3-642-57280-7_11, MILLIGAN, G.W., COOPER, M.C. (1988) doi:10.1007/BF01897163, JAJUGA, K., WALESIAK, M., BAK, A. (2003) doi:10.1007/978-3-642-55721-7_12, DAVIES, D.L., BOULDIN, D.W. (1979) doi:10.1109/TPAMI.1979.4766909, CALINSKI, T., HARABASZ, J. (1974) doi:10.1080/03610927408827101, HUBERT, L. (1974) doi:10.1080/01621459.1974.10480191, TIBSHIRANI, R., WALTHER, G., HASTIE, T. (2001) doi:10.1111/1467-9868.00293, BRECKENRIDGE, J.N. (2000) doi:10.1207/S15327906MBR3502_5, WALESIAK, M., DUDEK, A. (2008) doi:10.1007/978-3-540-78246-9_11).