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All in all, we present three new sampling strategies to improve on both variance and efficiency on the balance heuristic using non-equal count of samples.
The multi-sample estimators using the optimal distribution of samples obtained in Section 5 perform better than the multi-sample estimators defined in [11], in both variance and efficiency.
The optimal distribution of samples obtained in Section 5 performs always better for both the one-sample and the multi-sample estimator cases than the balance heuristic estimator with equal count of samples, in both variance and efficiency.
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As expected the multi-sample estimators defined in [11] (Section 2.2.1) are better than balance heuristic with equal count of samples, both in variance and efficiency.
Next, we examine a recently introduced non-balance heuristic MIS estimator that is provably better than balance heuristic with equal count of samples, and we improve it both in variance and efficiency.
Somewhat surprisingly, GHPS was only marginally superior to HPS in terms of sampling variance and efficiency.
Mix variance and efficiency variance allow us to separate out cost differences due to a different mix of personnel skill used in the care delivery from those due to the quantities of total personnel time used, respectively.
Precision is defined as small variance and relative efficiency is defined as smaller variance than other alternative.
Figure 14 Imputation variance and relative efficiency.
The performance will be assessed in terms of PSNR variance and compression efficiency for the two scenarios already used in the previous section, this means WZ video coding with and without quality control.
A linear probability model with individual, maternal, and household covariates included to reduce residual variance and improve efficiency was used for estimation.
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