A Novel Generalized Family of Distributions for Engineering and Life Sciences Data Applications

Table 1

Parameter estimates, MSEs, and biases.

Parameter	N				MSE	MSE	MSE	Bias	Bias	Bias
= 2	50	1.8313	1.9424	2.296	12.6804	0.2263	0.9513	−0.1686	−0.0575	0.2961
= 2	100	2.2109	1.9674	2.128	5.4230	0.0759	0.5266	0.2109	−0.0326	0.1276
= 2	500	2.4666	1.9495	1.897	2.4996	0.018613	0.2793	0.4666	−0.0505	−0.1033
	1000	2.1703	1.9687	1.963	1.0722	0.009575	0.12885	0.17027	−0.0312	−0.0367
= 3	50	2.1597	4.3702	6.654	19.3275	2.1949	9.3930	−0.8403	0.37028	1.6536
= 4	100	2.2010	4.0996	6.158	8.4937	0.8822	6.1319	−0.7989	0.09963	1.1583
= 5	500	2.7346	4.0784	5.399	1.6347	0.1976	1.67827	−0.26533	0.07847	0.39927
	1000	2.8663	4.0381	5.236	1.02057	0.1227	1.0413	−0.1336	0.03812	0.2345
= 3	50	1.7599	5.6261	8.274	15.6080	4.1271	14.2178	−1.2400	0.62619	2.2739
= 5	100	2.1047	5.5440	7.504	6.0097	2.3138	8.6038	−0.89527	0.54396	1.5035
= 6	500	2.7731	5.2123	6.501	1.6808	0.4410	2.0706	−0.2268	0.2123	0.5012
	1000	2.9212	5.0763	6.215	1.0373	0.2586	1.1940	−0.0787	0.07635	0.21453
= 5	50	2.0779	9.6075	3.298	47.0512	25.955	3.7047	−2.92211	2.60746	1.29763
= 7	100	2.7948	9.2775	3.066	27.6145	22.6489	2.96095	−2.20522	2.2775	1.06606
= 2	500	4.1762	7.7560	2.363	5.9401	4.4619	0.8725	−0.8237	0.75599	0.3619
	1000	4.7610	7.3345	2.133	2.14639	2.02909	0.34893	−0.23899	0.33452	0.13318