Sentence examples for variable regression modelling from inspiring English sources

This application of latent variable regression modelling techniques to intensive care datasets demonstrates high accuracy of prediction.

Also, it can be carried out in the presence of independent variable regression modeling where there is multicollinearity.

In a recent study, Roh et al. [5] conducted dummy variable regression modeling using vehicle classification data collected from WIM system.

For instance, King found through multi-variable regression modelling that the urine heme dipstick performed better in children than in mixed populations of adults and children (Relative diagnostic odds ratio = 3.16).

The first two parts are deterministic parts and are modeled separately with dummy variable regression models.

The results for the dummy variable regression model in (1) are reported in Table 2.

The data were then fitted by a multiple variable regression model using the maximum likelihood method.

In this paper a general framework to perform the inversion of latent variable regression models (LVRMs) is proposed.

The procedure starts by building a one variable regression model using the variable that has the highest correlation with the response variable y.

The dummy variable regression model is estimated for the value-weighted (VW), equally-weighted (EW), and 10 decile portfolios sorted by market capitalization.

Finally, from the final population and for each compound dataset, 3 9 variable regression models were built for the corresponding biological activity.