Examples of using Linear regression model in English and their translations into French
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based on standard statistical practice, the Panel concluded that a standard linear regression model should be used for the valuation of all C1-Money losses.
especially in the development of linear regression models.
The Regression Modeling study allows you to estimate a number of linear regression models for a given dependent variable that you want to describe,
Stochastic gradient descent has been used since at least 1960 for training linear regression models, originally under the name ADALINE.
Unfortunately,(22) is a nonlinear regression model whereas the earlier log-log and semilog models were linear regression models.
When both indicators are log transformed, power law relationships can be analyzed using linear regression models.
Claims containing outlier amounts claimed were excluded from the model building phases when developing the linear regression models used to value both C1-Money
In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear regression models.
Unfortunately,(30) is a nonlinear regression model whereas the earlier translog and semilog quadratic models were linear regression models.
Linear regression models were fitted to the samples from a Mediterranean case study in the northern(35o-55o N) and southern(25o-35o N) belts.
Linear regression model for assessment of uncertainties measurement.
Application of the linear regression model developed to resolve C4-MV repairs;
The better the fit of the linear regression model, the closer R2 is to 1.
we can reparameterize our theoretical model so that we end up with a linear regression model.
of the identified measures, Argentina reported the use of a linear regression model, and Armenia reported the use of a methodology which reflected the IPCC Guidelines source categories.
states that in a linear regression model in which the errors have expectation zero,
energy-dense food consumption were assessed by multivariable logistic and linear regression models adjusted for sociodemographic and lifestyle factors.
Quantitative analysis performed using linear regression models with mixed effects,
separate linear regression models were run for men and women from each generation.
According to the linear regression models, an increase of 25 per cent in the liquid asset ratio results in an increase of 15 basis points in spreads in the long run.