Table 2 MSE of stratified and calibrated memory-type ratio estimators based on EWMA statistic at various values of 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 | |||
---|---|---|---|---|---|---|---|
y* | \(\:{\widehat{\varvec{y}}}_{\varvec{m}\varvec{r}}\) | y* | \(\:{\widehat{\varvec{y}}}_{\varvec{m}\varvec{r}}\) | y* | \(\:{\widehat{\varvec{y}}}_{\varvec{m}\varvec{r}}\) | ||
0.05 | 10 | 0.003017 | 0.000235 | 0.005501 | 0.000364 | 0.009212 | 0.000552 |
20 | 0.001541 | 0.000118 | 0.002736 | 0.000180 | 0.004621 | 0.000273 | |
30 | 0.001012 | 0.000077 | 0.001854 | 0.000121 | 0.003065 | 0.000180 | |
50 | 0.000613 | 0.000047 | 0.001104 | 0.000072 | 0.001831 | 0.000108 | |
200 | 0.000151 | 0.000012 | 0.000275 | 0.000018 | 0.000459 | 0.000027 | |
500 | 0.000062 | 0.000005 | 0.000111 | 0.000007 | 0.000185 | 0.000011 | |
0.25 | 10 | 0.003201 | 0.000208 | 0.005116 | 0.000294 | 0.008549 | 0.000448 |
20 | 0.001614 | 0.000104 | 0.002532 | 0.000145 | 0.004228 | 0.000220 | |
30 | 0.001060 | 0.000069 | 0.001697 | 0.00097 | 0.002840 | 0.000147 | |
50 | 0.000643 | 0.000041 | 0.001015 | 0.000057 | 0.001678 | 0.000087 | |
200 | 0.000160 | 0.000010 | 0.000253 | 0.000014 | 0.000423 | 0.000022 | |
500 | 0.000065 | 0.000004 | 0.000101 | 0.000006 | 0.000170 | 0.000009 | |
0.50 | 10 | 0.002532 | 0.000136 | 0.004565 | 0.000203 | 0.007630 | 0.000321 |
20 | 0.001261 | 0.000067 | 0.002288 | 0.000102 | 0.003778 | 0.000158 | |
30 | 0.000842 | 0.000045 | 0.001508 | 0.000067 | 0.002502 | 0.000105 | |
50 | 0.000505 | 0.000027 | 0.000914 | 0.000040 | 0.001501 | 0.000062 | |
200 | 0.000012 | 0.000007 | 0.000225 | 0.000001 | 0.000379 | 0.000016 | |
500 | 0.000050 | 0.000003 | 0.000090 | 0.000004 | 0.00050 | 0.000006 | |
0.75 | 10 | 0.002230 | 0.000079 | 0.004001 | 0.000114 | 0.006730 | 0.000195 |
20 | 0.001105 | 0.000039 | 0.001986 | 0.000057 | 0.003302 | 0.000094 | |
30 | 0.000741 | 0.000026 | 0.001344 | 0.000038 | 0.002217 | 0.000062 | |
50 | 0.000437 | 0.000015 | 0.000793 | 0.000022 | 0.001331 | 0.000038 | |
200 | 0.000112 | 0.000004 | 0.000202 | 0.000006 | 0.000330 | 0.000009 | |
500 | 0.000045 | 0.000002 | 0.000080 | 0.000002 | 0.00031 | 0.000004 | |
0.95 | 10 | 0.001975 | 0.000034 | 0.003592 | 0.000045 | 0.006025 | 0.000094 |
20 | 0.000974 | 0.000076 | 0.001768 | 0.000021 | 0.002961 | 0.000045 | |
30 | 0.000664 | 0.000011 | 0.001182 | 0.000014 | 0.001982 | 0.000030 | |
50 | 0.000397 | 0.000007 | 0.000716 | 0.000008 | 0.001185 | 0.000017 | |
200 | 0.000098 | 0.000002 | 0.000177 | 0.000002 | 0.000296 | 0.000004 | |
500 | 0.000039 | 0.000001 | 0.000072 | 0.000001 | 0.000118 | 0.000002 |