This example shows how to build a menu system that enables you to perform nonlinear regression from a menu. Six modules are stored on an IML storage disk. After you have stored them, use this example ...

A nonlinear regression model sometimes fails to be close to linear due to the properties of a single parameter. When this occurs, bias in the parameters can render inferences using the reported ...

Walter Oberhofer, Harry Haupt, ASYMPTOTIC THEORY FOR NONLINEAR QUANTILE REGRESSION UNDER WEAK DEPENDENCE, Econometric Theory, Vol. 32, No. 3 (June 2016), pp. 686-713 ...

A method commonly used to fit non-linear curves to data instead of straight regression lines is polynomial regression. This method uses the same principles as linear regression but models the ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

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 ...

JUNGSIK NOH, SANGYEOL LEE, Quantile Regression for Location-Scale Time Series Models with Conditional Heteroscedasticity, Scandinavian Journal of Statistics, Vol. 43, No. 3 (September 2016), pp.