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Path loss models are used together with Gaussian processes to compute mean predictions and most importantly, to bound Gaussian processes' predicted variances.
We find that local-scale heterogeneity significantly increases predictive uncertainty in the percolation fluxes and tracer plumes, whereas the mean predictions are only slightly affected by the local-scale heterogeneity.
Now, I don't mean predictions of the type "third-quarter GDP will rise at an annual rate of 1.7 percent"; those things depend on a lot of detail, and a keen eye for the relevant details.
For deterministic (ensemble mean) predictions, the Percent Bias (PBias) is improved with integration of the DA.
Posterior mean predictions for September extent in 2012, 2013 and 2014 are respectively 3.88, 3.78 and 3.68mn k m2.
There is almost no noticeable difference in the unconditional Favre mean predictions by the CMC and SLFM.
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The first was the mean prediction error (MPE), which measures the bias and predictive accuracy, and the second was the mean absolute prediction error (MAPE): MPE=frac{1}{n}{displaystyle sum_{i=1}^nleft {y}_i-{widehat{y}}_iright)} MAPE=frac{1}{n}{displaystyle sum_{i=1}^nleft|{y}_i-{widehat{y}}_ikern0.1em right|}.
Created software product predicts about 400 kinds of biotransformation terms with the mean prediction accuracy of about 88%.
HbA1c percentage was predicted for each arm at end-of-trial with a mean prediction error of 0.14% [0.01 0.24].
The mean prediction was a 24% risk if interest rates remain steady, rising to a 39% risk if they go up again.
Mean prediction error.
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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