A New Conway Maxwell–Poisson Liu Regression Estimator—Method and Application

Table 11

Estimated MSEs of the COMPRM estimators, when and .

n	ρ	MLE
50	0.80	38.404	8.246	10.658	31.038	2.791	6.379	5.873	22.204	2.704	4.800	3.585	22.204	2.683
	0.90	75.664	17.029	22.077	62.182	2.286	9.684	8.480	42.438	2.126	5.659	3.519	42.438	2.072
	0.95	146.464	31.443	42.714	123.238	1.813	14.810	12.029	77.407	1.546	7.687	3.870	77.407	1.488
	0.99	825.357	229.695	291.175	764.568	4.637	79.137	72.707	442.749	1.014	31.209	13.356	442.749	0.875
100	0.80	17.129	3.564	4.313	11.940	2.614	3.551	3.559	9.981	2.614	3.389	2.944	9.981	2.614
	0.90	33.531	5.575	6.889	24.423	2.237	4.878	4.429	19.298	2.237	3.945	2.867	19.298	2.237
	0.95	57.956	8.758	11.115	43.818	1.631	6.420	5.144	30.367	1.630	4.495	2.638	30.367	1.627
	0.99	298.938	54.101	65.813	243.115	1.523	27.675	22.055	155.787	0.651	12.782	4.857	155.787	0.585
150	0.80	15.000	2.926	3.381	10.083	2.610	3.028	3.040	8.805	2.610	3.141	2.767	8.805	2.610
	0.90	30.021	4.622	5.950	21.384	2.316	4.567	4.219	17.626	2.316	3.928	2.863	17.626	2.316
	0.95	55.159	8.162	9.605	40.166	1.648	6.590	5.156	30.272	1.627	4.671	2.671	30.272	1.614
	0.99	265.768	43.810	48.122	215.129	1.372	24.921	20.050	142.975	0.604	11.193	4.603	142.975	0.558
200	0.80	14.472	3.015	3.412	9.664	2.766	3.073	3.183	8.747	2.766	3.231	2.917	8.747	2.766
	0.90	26.358	4.099	5.065	18.168	2.385	4.082	3.828	15.381	2.383	3.744	2.842	15.381	2.380
	0.95	51.232	7.292	8.963	35.943	1.786	6.412	5.437	29.013	1.783	4.680	2.863	29.013	1.781
	0.99	231.719	32.910	36.067	186.547	0.777	21.331	17.543	125.338	0.591	10.025	4.137	125.338	0.570