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In Fig. 10 b, we compare the estimation performance of the estimates of total 625×8=5000 pixels with the true gauge adjusted radar rainfall depths.
In Fig. 10 a, we compare the estimation performance of the estimates of the 625 pixels over eight snapshots, i.e., a total of 625×8=5000 pixels with the true gauge adjusted radar rainfall depths.
In this section, we compare the estimation performance of the matched CML-MoM estimator, the recursive CML-WMoM estimator, and the robust C-Tyler estimator with the CCRB, while the performance of the mismatched CMML estimator are compared with the CMCRB.
Finally, we compare the estimation performance of the proposed online power scheduling scheme with some typical offline power scheduling schemes.
This paper has presented a novel method to compare the estimation models and has provided a detailed analysis on available models.
In order to compare the estimation performance of the EKF and UKF, both observers are designed for the same motor model and run with the same covariance matrices under the same conditions.
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The goal of this collaborative effort is to use a weight-of-evidence (WOE) approach to estimate joint toxicity of some simple chemical mixtures and to compare the estimations with test results from animal toxicity studies.
We compare the estimations between data sets and between different CRISPR arrays present in a genome.
A Kolmogorov-Smirnov test was used on the 1% simulations retained to compare the estimations of the T parameter between varieties.
Note that we did not statistically compare the estimations of sensitivity and specificity due to the lack of standard statistical test.
For Loevinger's H coefficient (H) and Personal Separation Index (PSI), the biases in estimating these parameters are computed by comparing the estimation for each replication to the corresponding estimation obtained with complete datasets.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com