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It shows that the analytical model has relative high calculation accuracy.
The results show that the analytical model has relative high calculation accuracy.
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This model has an accelerated life interpretation (Lawless 2002), whereas the generalized log-logistic and Weibull PH models have relative risk interpretation.
The Y p/x was 481.2 U/g indicating that the model has a relative error of 4.8% for the confirmatory tests.
Also, the model has accurate relative contributions of different calcium transport mechanisms that cooperatively generate calcium signals with parameters like diastolic and systolic [Ca2+]i as well as decays of calcium transients corresponding to the measured average values from various sources (Table 2).
Our expanded model predictions had relative RMS errors within this range (9-21%).
Compared to most popular methods in cancer microarray gene expression data analysis area, rule-based fuzzy models usually have relative high computational complexity.
This method results in estimates of relative rates that are almost always similar to the relative hazards obtained from Cox regression models (and have relative hazard interpretation) but with the advantage of having a full likelihood available to measure goodness-of-fit.
The results show that the mean relative error of each individual submodel always lies within 10% of the physical measurements, while the complete model has a mean relative error of only 12%.
Moreover, the model has obtained the relative importance ordered of the variables which included x[gua] > temperature > x[MDEA] > x[H2O].
The models were found to have various degrees of relative error, with the best fitting model having a relative error of less than 10% for all three fuels with a marginal bias towards underestimation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com