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The software lets the fire brigade use a technique known as modelling regression to target places that register as at high risk for fire.
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Langmuir Hinshelwood rate equations were derived and discriminated through model regression to experimental data.
The study by Kan and Tsai [ 39] used ordered probit model regression to calculate coefficients of awareness of the health risks of obesity.
Last, we performed linear mixed models regression to compare evolution of hemoglobin and creatinine between both groups based on multiple imputations of missing values [ 23].
In developing the model, regression analysis to fit coefficients of the developed model is compared to the regression analysis results obtained from the experiment of the researchers.
There are two models of logistic regression to contain binomial/binary logistic regression and multinomial logistic regression.
The second approach uses linear regression to model annual concentrations.
Linear mixed model regression was used to analyze changes over time in plasma FABP levels.
We used generalized linear mixed-model regression in order to adjust for the school clustering effect.
We used general linear model regression (SAS 9.3) to evaluate changes over time in average comfort/experience scores.
In fact, within each model, regression coefficients tended to be very similar across training datasets that included the line itself.
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