Table 2 Simulations results for values of k = 0.1 and h = 0.8.

Methods of Estimation	Parameters	n = 20		n = 40		n = 75		n = 100		n = 200
Methods of Estimation	Parameters	RMSE	Bias	RMSE	Bias	RMSE	Bias	RMSE	Bias	RMSE	Bias
LM	\(\:\epsilon\:\)	3.9238	−3.2683	1.0071	−0.3839	0.4517	−0.1181	0.3326	−0.0621	0.1854	−0.0052
	\(\:\theta\:\)	6.4600	5.4247	1.3791	0.4401	0.568	0.1478	0.39	0.0859	0.228	0.015
	K	0.8930	0.7948	0.2638	0.0516	0.1980	0.0321	0.1470	0.0208	0.1026	−0.0045
	H	1.1167	0.0517	0.6349	0.1619	0.4280	0.0313	0.3386	0.0140	0.2098	−0.0173
MLE	\(\:\epsilon\:\)	1.3031	−1.164	1.3735	−0.8295	0.4849	−0.2332	0.3439	−0.1300	0.1366	−0.038
	\(\:\theta\:\)	2.9525	2.2641	2.0332	1.2175	0.6982	0.352	0.4829	0.2074	0.2045	0.0546
	K	0.8686	0.6922	0.3691	0.2881	0.2365	0.1261	0.1761	0.0880	0.0922	0.0223
	H	0.7240	0.5238	0.6651	0.4038	0.3518	0.1616	0.2558	0.1001	0.1248	0.0357
MPS	\(\:\epsilon\:\)	0.7771	−0.4771	0.3517	0.1842	0.2555	0.0267	0.2043	0.0095	0.1141	0.0265
	\(\:\theta\:\)	0.5314	0.5313	0.3067	−0.2911	0.31	−0.0364	0.2673	0.0032	0.1682	−0.0352
	K	0.1542	0.1542	0.1912	−0.1556	0.1793	−0.0566	0.1414	−0.0310	0.0959	−0.0432
	H	0.7039	0.2540	0.4856	−0.3028	0.3476	−0.0987	0.2255	−0.0417	0.1317	−0.0433

Note: The lowest values of RMSE and Bias for “k” and “h” and different sample sizes are highlighted in red.

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