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

Table 10

Estimated MSEs of the COMPRM estimators, when and .

n	ρ	MLE
50	0.80	27.497	5.947	7.595	21.386	3.146	5.244	4.976	15.810	3.146	4.512	3.735	15.810	3.146
	0.90	52.869	10.614	13.437	41.887	2.659	7.178	6.129	28.850	2.588	5.115	3.554	28.850	2.572
	0.95	106.088	22.046	28.633	86.902	2.126	11.565	9.287	55.410	2.053	6.748	3.817	55.410	2.033
	0.99	608.777	158.674	195.964	554.233	3.151	57.575	54.380	314.720	1.292	24.800	11.381	314.720	1.133
100	0.80	12.262	3.357	3.629	8.526	3.097	3.417	3.454	7.463	3.097	3.453	3.217	7.463	3.097
	0.90	23.600	4.372	5.235	16.612	2.986	4.278	4.144	13.613	2.986	4.051	3.376	13.613	2.986
	0.95	41.674	6.419	7.971	30.241	2.450	5.435	4.524	22.509	2.450	4.492	3.103	22.509	2.450
	0.99	207.263	34.141	39.641	162.777	1.542	19.643	15.414	107.984	1.052	10.074	4.277	107.984	1.010
150	0.80	10.851	3.210	3.365	7.266	3.158	3.234	3.285	6.628	3.158	3.366	3.214	6.628	3.158
	0.90	21.165	3.883	4.630	14.680	3.157	4.066	3.938	12.739	3.157	4.073	3.401	12.739	3.157
	0.95	38.878	5.544	6.719	27.381	2.550	5.407	4.757	21.860	2.550	4.701	3.305	21.860	2.550
	0.99	191.155	30.284	33.287	151.939	1.319	19.199	15.512	104.619	1.033	9.524	4.138	104.610	0.985
200	0.80	10.131	3.225	3.338	6.760	3.187	3.233	3.292	6.362	3.187	3.324	3.228	6.362	3.187
	0.90	18.636	3.768	4.300	12.620	3.282	3.871	3.893	11.235	3.282	3.988	3.494	11.235	3.282
	0.95	35.977	5.082	6.163	24.534	2.793	5.270	4.679	20.948	2.793	4.744	3.415	20.948	2.793
	0.99	170.120	24.371	26.463	132.767	1.115	17.376	14.696	95.954	1.067	9.008	4.164	95.954	1.059