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

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 ...

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

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, although ...

Thus, you should use caution in interpreting these statistics for nonlinear models, especially for small sample sizes. For linear models, these results are exact and are the same as standard linear ...

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 A. K. Suykens and Joao Garcia ...