Table 1.

Classification error and computation time for various clustering methods applied to simulated data.

Classification Error (%)
	J	HC	DynTree	HOPACH (best)	HOPACH (greedy)	MM(1–6)	RPMM (ICL-BIC)	RPMM (BIC)
Case 1	25	33.2	44.7	9.9	16.4	12.6	15.5	15.4
	50	32.5	43.8	5.0	10.0	6.2	5.5	5.5
	500	33.9	38.4	3.5	11.3	1.5	0.1	0.1
	1000	34.0	38.5	9.2	14.4	1.1	0.1	0.1
Case 2	5	59.4	60.5	65.1	65.8	59.4	59.4	59.4
	10	58.9	60.0	66.9	67.5	59.2	59.2	59.2
	25	30.0	39.6	4.1	8.1	0.0	0.0	0.0
	50	29.9	39.6	3.6	6.4	0.3	0.3	0.3
Computation Time (seconds)
	J	HC	DynTree	HOPACH (best)	HOPACH (greedy)	MM(1–6)	RPMM (ICL-BIC)	RPMM (BIC)
Case 1	25	0.00	0.04	4.15	1.18	36.39	13.80	13.83
	50	0.01	0.05	3.29	1.09	51.14	14.23	14.23
	500	0.03	0.08	2.98	1.04	436.82	90.99	91.05
	1000	0.06	0.11	3.05	1.10	848.10	176.99	176.81
Case 2	5	0.00	0.04	2.80	1.21	29.73	5.14	6.09
	10	0.00	0.04	2.01	1.13	46.48	9.69	10.05
	25	0.00	0.01	3.33	1.23	34.56	8.85	8.86
	50	0.01	0.01	2.63	1.16	47.52	10.90	10.86

HC = Hierarchical clustering

DynTree = Hierarchical clustering with classes determined by dynamic tree cutting

HOPACH(best) = HOPACH with 'best' number of classes

HOPACH(greedy) = HOPACH with 'greedy' number of classes

MM(1–6) = Beta mixture model fitting 1–6 classes sequentially

RPMM (ICL-BIC) = Recursively partitioned mixture model employing ICL-BIC

RPMM (BIC) = Recursively partitioned mixture model employing BIC

J = Number of loci considered in analysis