Table 7 MSE of memory-type and proposed calibrated ratio estimators based on EWMA statistic at different values of correlation coefficient ρ, smoothing parameters \(\:\lambda\:=0.50,\:0.75,\:1.00,\) and sample sizes \(\:n\).
From: Innovative memory-type calibration estimators for better survey accuracy in stratified sampling
ρ | n | λ = 0.50 | λ = 0.75 | λ = 1.00 | |||
---|---|---|---|---|---|---|---|
\(\:{{\stackrel{-}{y}}^{M}}_{rt}\) | \(\:{\widehat{y}}_{mr}\) | \(\:{{\stackrel{-}{y}}^{M}}_{rt}\) | \(\:{\widehat{y}}_{mr}\) | \(\:{{\stackrel{-}{y}}^{M}}_{rt}\) | \(\:{\widehat{y}}_{mr}\) | ||
0.05 | 10 | 0.034272 | 0.000238 | 0.060639 | 0.000360 | 0.102756 | 0.000550 |
20 | 0.016875 | 0.000118 | 0.030154 | 0.000179 | 0.051011 | 0.000271 | |
30 | 0.011274 | 0.000078 | 0.020349 | 0.000120 | 0.034238 | 0.000182 | |
50 | 0.006762 | 0.000047 | 0.012311 | 0.000072 | 0.020533 | 0.000109 | |
200 | 0.001675 | 0.000011 | 0.003023 | 0.000018 | 0.005123 | 0.000027 | |
500 | 0.000675 | 0.000005 | 0.001223 | 0.00007 | 0.002036 | 0.000011 | |
0.25 | 10 | 0.030790 | 0.000187 | 0.056942 | 0.000294 | 0.094406 | 0.000448 |
20 | 0.015782 | 0.000096 | 0.028117 | 0.000144 | 0.046566 | 0.000217 | |
30 | 0.010341 | 0.000063 | 0.018855 | 0.000047 | 0.031303 | 0.000146 | |
50 | 0.006321 | 0.000038 | 0.011214 | 0.000057 | 0.018731 | 0.000088 | |
200 | 0.001582 | 0.000009 | 0.002846 | 0.000014 | 0.004683 | 0.000022 | |
500 | 0.000623 | 0.000004 | 0.001133 | 0.000006 | 0.001884 | 0.000009 | |
0.50 | 10 | 0.028151 | 0.000137 | 0.050739 | 0.000204 | 0.084447 | 0.000318 |
20 | 0.013849 | 0.000066 | 0.025016 | 0.000100 | 0.041823 | 0.000157 | |
30 | 0.009345 | 0.000045 | 0.016780 | 0.000067 | 0.027691 | 0.000104 | |
50 | 0.005517 | 0.000026 | 0.010098 | 0.000040 | 0.016826 | 0.000063 | |
200 | 0.0013888 | 0.000007 | 0.002529 | 0.000010 | 0.004191 | 0.000015 | |
500 | 0.000553 | 0.000003 | 0.001008 | 0.00004 | 0.001675 | 0.000006 | |
0.75 | 10 | 0.024390 | 0.000078 | 0.045117 | 0.000116 | 0.074298 | 0.000899 |
20 | 0.012351 | 0.000039 | 0.022149 | 0.000056 | 0.036806 | 0.000441 | |
30 | 0.008139 | 0.000026 | 0.014919 | 0.000037 | 0.024565 | 0.000295 | |
50 | 0.004925 | 0.000016 | 0.008910 | 0.000022 | 0.014832 | 0.000177 | |
200 | 0.001226 | 0.00004 | 0.002186 | 0.000006 | 0.003114 | 0.00004 | |
500 | 0.000498 | 0.000002 | 0.000882 | 0.00002 | 0.001493 | 0.00002 | |
0.95 | 10 | 0.021876 | 0.000034 | 0.039365 | 0.000044 | 0.066528 | 0.000094 |
20 | 0.011011 | 0.000017 | 0.019648 | 0.000021 | 0.032561 | 0.000044 | |
30 | 0.007382 | 0.000011 | 0.013224 | 0.000014 | 0.022141 | 0.000030 | |
50 | 0.004332 | 0.00007 | 0.007934 | 0.000008 | 0.013277 | 0.000018 | |
200 | 0.001103 | 0.000002 | 0.001990 | 0.000002 | 0.003299 | 0.000004 | |
500 | 0.000442 | 0.000007 | 0.000791 | 0.000001 | 0.001332 | 0.000002 |