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From the results it is observed that both AMS and PDS models yield the same variance when μ varies from 1.4 to 1.65.
Two models yield the essentially same results for the weak nonlinearity, the small axial speed and the low mode, while the difference between two models increases with the nonlinear term, the axial speed, and the order of mode.
Mechanistic models yield the highest explanatory power for the effects of climate changes, and thus have optimal assessment effectiveness.
It was demonstrated that the QuBiLS-MIDAS models yield the best predictions, and that these are significantly superior in 11 of the 12 methodologies compared.
These quadratic models yield the best possible fit to the data and lowest possible RMS value.
The amplitude and the position of these models yield the signals and position of the photoactivated spindle as well as the signal intensity background spindle.
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However, since in none of the analyses did any significant covariate term remain, these models yielded the same results as the repeated measures ANOVAs (not shown).
The three models yielded the following results.
In all these analyses, BayesB and SPLS models yielded the highest accuracies, followed by BL, whereas RR-BLUP and PLS models yielded the lowest accuracies.
The forward selection models yielded the highest model R2 for both the RARBIS with medications (R2 = 0.31) and the RARBIS without medications (R2 = 0.26).
The results of our model yield the above range in L C values.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com