Table 2.

Means of estimates of the parameters and MSEs (in parentheses) for many estimation methods when n = 30.

n	α	β	${\hat{\alpha }}_{\mathrm{ML}}$	${\hat{\beta }}_{\mathrm{ML}}$	${\hat{\alpha }}_{\mathrm{B}}$	${\hat{\beta }}_{\mathrm{B}}$	${\hat{\alpha }}_{\mathrm{LS}}$	${\hat{\beta }}_{\mathrm{LS}}$	${\hat{\alpha }}_{\mathrm{WLS}}$	${\hat{\beta }}_{\mathrm{WLS}}$	${\hat{\alpha }}_{\mathrm{MPS}}$	${\hat{\beta }}_{\mathrm{MPS}}$	${\hat{\alpha }}_{\mathrm{P}}$	${\hat{\beta }}_{\mathrm{P}}$	${\hat{\alpha }}_{\mathrm{AD}}$	${\hat{\beta }}_{\mathrm{AD}}$	${\hat{\alpha }}_{\mathrm{RAD}}$	${\hat{\beta }}_{\mathrm{RAD}}$
30	0.75	0.75	0.8248	0.8421	0.8131	0.8093	0.7648	0.7694	0.7743	0.7838	0.7355	0.707	0.7602	0.7459	0.7835	0.797	0.8021	0.8734
			(0.0346)	(0.0686)	(0.0294)	(0.0520)	(0.0388)	(0.0871)	(0.0344)	(0.0759)	(0.0213)	(0.0464)	(0.0472)	(0.0759)	(0.0322)	(0.0647)	(0.0380)	(0.1732)
		1.5	0.8326	1.6937	0.8329	1.6944	0.7663	1.5435	0.7779	1.578	0.7432	1.4237	0.7588	1.465	0.7873	1.6026	0.8084	1.77
			(0.0354)	(0.2803)	(0.0323)	(0.2233)	(0.0384)	(0.3497)	(0.0336)	(0.3079)	(0.0207)	(0.1859)	(0.0499)	(0.2286)	(0.0322)	(0.2621)	(0.0381)	(0.7220)
		2.5	0.8409	2.8462	0.8214	2.6558	0.7682	2.5903	0.7822	2.6579	0.7514	2.3954	0.7545	2.4078	0.7917	2.6935	0.8147	2.9966
			(0.0363)	(0.7761)	(0.0280)	(0.4083)	(0.0366)	(0.9924)	(0.0317)	(0.8855)	(0.0202)	(0.4971)	(0.0565)	(0.6103)	(0.0318)	(0.7327)	(0.0376)	(2.1468)
	1.5	0.75	1.6323	0.8032	1.548	0.7687	1.5357	0.7525	1.551	0.7624	1.4179	0.7005	1.5055	0.7427	1.5678	0.7725	1.5955	0.7977
			(0.1813)	(0.0335)	(0.1171)	(0.0254)	(0.2034)	(0.0403)	(0.1823)	(0.0357)	(0.1197)	(0.0270)	(0.1701)	(0.0473)	(0.1666)	(0.0322)	(0.1978)	(0.0548)
		1.5	1.6316	1.6031	1.5746	1.5803	1.5358	1.5019	1.5508	1.5215	1.417	1.3978	1.5052	1.4717	1.5667	1.5417	1.5966	1.5943
			(0.1820)	(0.1357)	(0.1234)	(0.1059)	(0.2152)	(0.1603)	(0.1917)	(0.1425)	(0.1200)	(0.1110)	(0.1660)	(0.1266)	(0.1683)	(0.1294)	(0.2029)	(0.2169)
		2.5	1.6357	2.6806	1.5395	2.5318	1.5361	2.5089	1.5515	2.5421	1.4208	2.338	1.4957	2.427	1.569	2.5766	1.5975	2.6627
			(0.1810)	(0.3730)	(0.1086)	(0.2333)	(0.2034)	(0.4479)	(0.1822)	(0.3968)	(0.1182)	(0.2992)	(0.1764)	(0.3265)	(0.1666)	(0.3584)	(0.1977)	(0.6098)
	2.5	0.75	2.7646	0.7917	2.7206	0.7784	2.5881	0.7479	2.6136	0.7566	2.341	0.7019	2.4773	0.7306	2.6389	0.7649	2.6989	0.7826
			(0.6938)	(0.0246)	(0.4343)	(0.0193)	(0.8772)	(0.0290)	(0.7596)	(0.0257)	(0.4181)	(0.0212)	(0.6223)	(0.0390)	(0.6241)	(0.0234)	(0.7769)	(0.0340)
		1.5	2.7649	1.5835	2.7689	1.5904	2.5882	1.4958	2.6137	1.5132	2.3413	1.4038	2.486	1.468	2.6392	1.5299	2.6992	1.5653
			(0.6939)	(0.0985)	(0.4657)	(0.0804)	(0.8773)	(0.1160)	(0.7596)	(0.1030)	(0.4178)	(0.0847)	(0.4900)	(0.0922)	(0.6242)	(0.0937)	(0.7770)	(0.1359)
		2.5	2.7706	2.6458	2.7033	2.576	2.5877	2.4973	2.6141	2.5268	2.3466	2.3462	2.4768	2.4326	2.6432	2.5553	2.6991	2.6119
			(0.6900)	(0.2715)	(0.4012)	(0.1828)	(0.8102)	(0.3223)	(0.7091)	(0.2850)	(0.4132)	(0.2295)	(0.4893)	(0.2311)	(0.6191)	(0.2591)	(0.7557)	(0.3790)