A Unit Probabilistic Model for Proportion and Asymmetric Data: Properties and Estimation Techniques with Application to Model Data from SC16 and P3 Algorithms

Table 2

Simulation results of Log-XLindley distribution at

	Measure	MLE	LSE	WLE	CVME	ADE	RADE	MPSE
10	AVEs	1.0837	1.0606	1.0591	1.0682	1.0498	1.1083	0.9891
25		1.0282	1.0207	1.0166	1.0224	1.0163	1.0404	0.9802
50		1.0139	1.0141	1.0098	1.0117	1.0109	1.0154	0.9871
100		1.0058	1.0061	1.0054	1.0073	1.0034	1.0102	0.9896
150		1.0041	1.0046	1.0038	1.0056	1.0024	1.0055	0.9914
200		1.0042	1.0024	1.0019	1.0032	1.0022	1.0049	0.9941
10	AABs	0.0837	0.0606	0.0591	0.0682	0.0498	0.1083	0.0109
25		0.0282	0.0207	0.0166	0.0224	0.0163	0.0404	0.0198
50		0.0139	0.0141	0.0098	0.0117	0.0109	0.0154	0.0129
100		0.0058	0.0061	0.0054	0.0073	0.0034	0.0102	0.0104
150		0.0041	0.0046	0.0038	0.0056	0.0024	0.0055	0.0086
200		0.0042	0.0024	0.0019	0.0032	0.0022	0.0049	0.0059
10	MREs	0.0837	0.0606	0.0591	0.0682	0.0498	0.1083	0.0109
25		0.0282	0.0207	0.0166	0.0224	0.0163	0.0404	0.0198
50		0.0139	0.0141	0.0098	0.0117	0.0109	0.0154	0.0129
100		0.0058	0.0061	0.0054	0.0073	0.0034	0.0102	0.0104
150		0.0041	0.0046	0.0038	0.0056	0.0024	0.0055	0.0086
200		0.0042	0.0024	0.0019	0.0032	0.0022	0.0049	0.0059
10	MSEs	0.1053	0.1386	0.1348	0.1289	0.0935	0.1907	0.0722
25		0.0301	0.0402	0.0326	0.0389	0.0334	0.0520	0.0271
50		0.0139	0.0180	0.0161	0.0174	0.0158	0.0218	0.0132
100		0.0063	0.0085	0.0077	0.0084	0.0071	0.0102	0.0062
150		0.0042	0.0057	0.0050	0.0055	0.0049	0.0066	0.0042
200		0.0033	0.0041	0.0037	0.0040	0.0037	0.0050	0.0032