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AIC estimates are compared and the model with the lower AIC is chosen.
The simulation results were compared and the model calibrated with water surface elevation records of the previous floods.
The measured and predicted baseflow values were then compared and the model parameters adjusted to improve the model calibration.
To select the best model among the four learning classifiers, the best models among the four learning classifiers are compared and the model obtaining the highest evaluation score is generally selected the best among the five gene selection methods and the four learning classifiers.
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Several models were compared and the models correcting for kinship (K) and two to three principal components (PCAs) fitted our data best, had the lowest inflation-factor and therefore the lowest false-discovery rate.
Different models are compared and the "best" model is chosen by a likelihood ratio test.
For the identification of expression trends, five regression models were compared and the quadratic model was found as the most suitable for this study.
Models will be compared and the best model will be selected on the basis of likelihood ratio tests.
Obtained model results for every refrigerant were compared and the best model was investigated.
The protein sequences were compared and modeled, and the putative motifs and domains were characterized.
We then compare and rank the models by classical measures of fit based on information criteria.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com