Your English writing platform
Discover LudwigSuggestions(5)
Exact(1)
Using simple linear regression with 24hU volume as a singular predictor, the percentage of variance in total fluid intake explained by the model was slightly lower (R=52%), but with a comparable root mean square error (629 ml) and 95% limits of agreement (−1238 1238 ml).
Similar(59)
The comparison showed that the bias results produced by the proposed method were far superior to the other methods trialled and other error statistics such as root mean square error were comparable or better (although the kriging methods tended to perform better in densely gauged areas).
The root mean square roughness of the sample observed from atomic force microscopic analysis is about 71.5 nm which is comparable to the average grain size of the coatings which is about 72 nm obtained from X-Ray diffraction.
Rq = root mean square roughness.
The root mean square (r.m.s).
(root mean square) and peak displacements, respectively.
A root mean square error of 0.6 °C was obtained.
All models gave similar root mean square error values.
Root mean square error was found out as 1.56.
The root mean square difference (RMSD) was 0.0843.
The root mean square deviation was less than 0.02.
Write better and faster with AI suggestions while staying true to your unique style.
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