A Nonconventional Auxiliary Information Based Robust Class of Exponential-type Difference Estimators

Table 5

Mean squared error of the proposed estimators.

Estimators	n = 3		n = 5
	Population.1	Population.2	Population.3	Population.4
	24567.500	24567.500	8911.906	8911.906
	24567.730	24567.740	8911.936	8911.936
	24567.640	24567.640	8911.923	8911.923
	24567.760	24567.760	8911.939	8911.939
	24567.440	24567.440	8911.899	8911.899
	24567.600	24567.600	8911.918	8911.918
	24524.790	24524.130	8906.486	8906.401
	24519.450	24520.560	8905.806	8905.948
	24513.570	24516.400	8905.058	8905.418
	24528.270	24527.650	8906.928	8906.848
	24523.200	24524.260	8906.283	8906.418
	24517.580	24520.290	8905.568	8905.913
	24494.490	24493.300	8902.629	8902.478
	24487.960	24488.940	8901.798	8901.922
	24481.300	24484.090	8900.949	8901.305
	24489.410	24490.410	8900.479	8900.602
	24482.910	24486.050	8899.692	8900.068
	24476.370	24481.240	8898.925	8899.493
	24491.240	24490.400	8900.812	8900.708
	24484.720	24486.040	8900.011	8900.171
	24478.130	24481.230	8899.226	8899.592