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For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized.
It is clear that the simulation error is in the range of 0 20% (Table 5), which is acceptable for numerical simulations.
The (f=5) PRISM simulation error is approximately 0.005% for all scattering angles, indicating that this simulation is essentially error-free.
The model-based error is the square root of the average of 1,000 squared estimated SEs of the pooled risk estimates, whereas the simulation error is the SD of 1,000 pooled risk estimates.
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Example outputs are shown and sources of simulation error are quantified.
In the AHGA, a weighted sum of scaled simulation errors is designed as an overall objective function to measure the fitness of solutions (i.e., parameter values).
As shown by the comparison between experimental and simulation results, the model error is restricted to ±1%, corresponding to a maximum absolute model error of 0.6 V.
The simulation errors were estimated and compared favorably with real-world headlight brightness variability.
During our evaluation, the needle positioning error was found to be within 0.153±0.042 mm of desired placement; the phantom simulation errors were within 0.693±0.128 mm.
Simulation errors were small despite the high sensitivity of the water balance model to precipitation, which in the historical period was that of a non-local station.
Because measurement and simulation errors are unavoidable, we usually prefer robust models and robust parameter settings.
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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