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When the fitting is good, the fitted area of each component can be used as an estimation of its probability.
To find out what is the difference between the actual object and the fitted curve and how the fitting is helping to get a better scan, a simulation was used.
When fitting a single sublattice, the fitting is done on individual atomic column using a single 2D Gaussian.
We tried to fit the data to single exponentials, and found that the fitting is statistically poorer than a double exponential based on the F-test.
It is noted that the R2 of the fitting is not too high (R2 = 0.7212) because the curve is fitted from only 4 data.
The fitting is achieved proposing two homogeneous sources of emission.
When the fitting is hot, remove the flame and touch the joint with the solder.
Now the energy range used in the fitting is restricted using the stack version of the Sherpa ignore command.
With a third-order model, the fitting is found to be encouraging and the best possible set of coefficients of the model transfer function is estimated.
At least two components are needed to de-convolute the NMR peak, one sharp and one broad (the fitting is explained in Supplementary Fig. 16), with the latter component diminishing at higher temperatures.
It is found that the adjusted coefficient of determination of the Nusselt number and friction coefficient is 0.943 and 0.999, respectively, which illustrate the fitting is correct and reliable.
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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