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

Table 4

Estimated MSEs of the COMPRM estimators, when and .

n	ρ	MLE
50	0.80	6.243	1.966	2.272	4.350	1.639	1.952	2.061	3.707	1.639	1.963	1.836	3.707	1.637
	0.90	11.699	2.880	3.773	8.017	1.626	2.596	2.674	6.378	1.592	2.394	2.035	6.378	1.584
	0.95	21.775	4.583	6.182	15.220	1.361	3.332	3.190	10.759	1.339	2.757	2.029	10.759	1.312
	0.99	115.68	27.424	36.194	96.248	2.573	13.137	13.090	57.966	0.852	7.940	5.354	57.966	0.764
100	0.80	4.121	1.624	1.756	2.703	1.544	1.617	1.706	2.515	1.544	1.650	1.625	2.515	1.544
	0.90	7.594	1.903	2.313	4.778	1.545	1.899	2.039	4.269	1.544	1.938	1.760	4.269	1.541
	0.95	16.466	3.174	4.388	11.151	1.649	3.066	3.123	9.416	1.580	2.736	2.099	9.416	1.541
	0.99	73.205	12.226	15.666	55.673	1.219	8.718	7.980	38.755	0.732	5.431	2.823	38.755	0.691
150	0.80	3.627	1.502	1.554	2.235	1.482	1.502	1.537	2.130	1.482	1.527	1.514	2.130	1.482
	0.90	6.612	1.643	1.888	3.897	1.551	1.684	1.802	3.642	1.551	1.788	1.678	3.642	1.551
	0.95	13.081	2.444	2.776	8.583	1.478	2.328	2.141	7.344	1.462	2.271	1.696	7.344	1.456
	0.99	61.972	9.910	11.796	45.699	1.116	7.444	7.303	32.304	0.704	4.915	2.922	32.304	0.678
200	0.80	3.583	1.499	1.557	2.239	1.487	1.496	1.545	2.161	1.482	1.524	1.510	2.161	1.477
	0.90	5.664	1.518	1.670	3.310	1.408	1.524	1.606	3.062	1.408	1.581	1.500	3.062	1.408
	0.95	12.371	2.214	2.787	7.658	1.623	2.317	2.372	6.796	1.611	2.360	1.936	6.796	1.607
	0.99	53.049	7.243	8.159	37.573	1.108	6.161	5.582	27.436	0.694	4.107	2.144	27.436	0.661