Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Nonlinear Regression Analysis . One of the most important uses of PROC MODEL is to estimate unknown parameters in a nonlinear model. A simple nonlinear model has the form: where x is a vector of ...

Nature is marked not only by struggles for survival, but also by remarkable feats of cooperation. From microbes to insects to humans, organisms work together in a variety of ways to gather and share ...

Nonlinear Regression: The NLIN Procedure . The NLIN procedure implements iterative methods that attempt to find least-squares estimates for nonlinear models. The default method is Gauss-Newton, ...

The new method fits 1/a heteroscedatic rather than a homoscedastic regression model and consider 2/non linear instead of linear regression.

In univariate nonlinear regression models, estimator and test statistics based on (generalized) least squares and maximum likelihood methods are usually nonrobust; M-procedures are better in this ...

Linear and non-linear credit scoring by combining logistic regression and support vector machines Tony Van Gestel, Bart Baesens, Peter Van Dijcke, Johan ... are less straightforward to interpret but ...