TABLE 1.

Performance of multiple robust estimators compared with WGEE estimators under 500 Monte Carlo data (all numbers listed in the table are multiplied by 100)

Setups	Method	β 0				β 1				β 2
		RB	SD	AB	RMSE	RB	SD	AB	RMSE	RB	SD	AB	RMSE
n = 400	WGEE_100	3.4	13.2	10.8	13.3	1.4	17.6	14.0	17.6	0.3	15.7	12.5	15.7
m = 0.3	WGEE_010	13.8	13.0	11.9	14.7	2.0	18.0	14.3	18.1	1.4	16.2	12.9	16.3
	MULTI_100	0.9	11.8	9.4	11.8	0.6	15.9	12.5	15.8	2.3	14.1	11.1	14.2
	MULTI_111	1.2	11.7	9.4	11.8	0.8	15.9	12.6	15.9	2.3	14.1	11.0	14.1
	MULTI_001	2.3	11.8	9.5	11.8	0.6	15.9	12.6	15.9	2.4	14.1	11.1	14.2
	MULTI_011	1.4	11.8	9.4	11.8	0.8	15.9	12.6	15.9	2.3	14.1	11.1	14.1
n = 700	WGEE_100	3.9	9.4	7.7	9.6	0.3	13.2	10.5	13.2	0.3	12.0	9.6	12.0
m = 0.3	WGEE_010	13.7	9.9	9.8	12.0	1.3	13.9	11.3	13.9	0.4	12.8	10.2	12.8
	MULTI_100	0.3	9.2	7.5	9.2	0.1	12.5	10.0	12.5	0.9	11.5	9.3	11.5
	MULTI_111	0.0	9.1	7.4	9.1	0.3	12.4	9.9	12.4	0.9	11.5	9.3	11.5
	MULTI_001	1.0	9.2	7.4	9.2	0.1	12.5	10.0	12.5	1.0	11.5	9.3	11.5
	MULTI_011	0.2	9.1	7.4	9.1	0.3	12.4	9.9	12.4	1.0	11.5	9.3	11.5
n = 400	WGEE_100	3.8	19.3	15.3	19.3	1.7	24.8	19.3	24.8	1.4	24.7	19.4	24.7
m = 0.5	WGEE_010	27.9	24.1	22.1	27.9	2.5	32.3	25.4	32.3	2.8	32.5	26.0	32.6
	MULTI_100	0.4	13.5	10.6	13.4	0.8	17.5	13.7	17.5	2.4	17.0	13.6	17.0
	MULTI_111	0.5	13.5	10.6	13.5	0.7	17.6	13.8	17.6	2.5	17.1	13.6	17.1
	MULTI_001	1.8	13.4	10.6	13.4	0.7	17.5	13.8	17.5	2.7	16.9	13.5	17.0
	MULTI_011	0.9	13.5	10.6	13.5	0.8	17.5	13.8	17.5	2.7	17.0	13.5	17.0
n = 700	WGEE_100	4.0	13.8	11.2	13.9	0.4	19.2	15.4	19.2	0.6	18.7	15.0	18.7
m = 0.5	WGEE_010	26.3	17.9	18.0	22.2	0.4	24.9	20.0	24.9	0.1	25.6	20.2	25.6
	MULTI_100	0.9	10.4	8.3	10.4	0.1	13.9	11.2	13.9	0.8	13.6	10.9	13.6
	MULTI_111	0.5	10.4	8.3	10.4	0.0	13.9	11.1	13.9	0.7	13.7	10.9	13.7
	MULTI_001	0.5	10.4	8.3	10.4	0.0	13.9	11.1	13.9	0.8	13.6	10.9	13.6
	MULTI_011	0.2	10.4	8.3	10.4	0.1	13.9	11.2	13.9	0.8	13.7	10.9	13.6