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Full factorial design of experiment revealed a very good fit of data.
Results showed the linear fit of data into the isotherm equations and hence the favourable isotherms.
Further, the fit of data to the intraparticle diffusion model was poor (R 2 ≤ 0.11).
The dashed line in the inset of Figure 5 is the least square fit of data with Equation 1.
We ran MEMFIT to get the best fit of data recorded in the ICU controls and the CIP patients.
From the slope and intercept of linear fit of data presented in Fig. 6, ∆Q max could be estimated.
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The TGI model provided an adequate fit of the data (data not shown).
Fitting of data to the above model indicate that CD, in general, is a function of the Reynolds number (Re).
New developments in two main data analysis areas are discussed: (a) complex nonlinear least squares (CNLS) fitting of data and (b) data-transforming and optimizing integral transforms.
In the least-squares fitting of data, there is a unique answer to the question of how the data should be weighted: inversely as their variance.
Another matrix decomposition algorithm which, among other uses, computes the least squares fitting of data, is the Singular Value Decomposition (SVD).
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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