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Smaller values χ 2 indicate smaller error.
Our full model yields a smaller error.
Also, the stations with more neighbors have smaller error ellipses.
If the ratio is smaller, error rates in comparing magnitudes spike up.
Training under CTA data arrays produced smaller error values than those for NTA.
At least one of OPT098 or OPT093 gives a smaller error than WELCHopt, SINopt, and THOMopt.
In real world, nodes with smaller error norm are preferred for a fast convergence.
Then it is better to choose nodes with smaller error norm.
Simulations using this model showed a significantly smaller error than the DLT model.
The robust distance measures result in smaller error rates than the Euclidean distance.
The smoothness of r ( x ) increases, and the smaller error can be derived.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com