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 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 ...

This article develops three empirical likelihood (EL) approaches to estimate parameters in nonlinear regression models in the presence of nonignorable missing responses. These are based on the inverse ...

9.1 Linear Regression 9.1.1 Review of the basics The lm function in R constructs—as its name implies—a linear model from data. Recall that a linear model is of the form Y = β0+β1X1+...+βnXn Y = β 0 + ...

The demo program creates a linear ridge regression model using the training data. The model uses a parameter named alpha, which is set to 0.05. The alpha value is the "ridge" part of "linear ridge ...

Yuanzhi Huang, Steven G. Gilmour, Kalliopi Mylona, Peter Goos, Optimal design of experiments for non-linear response surface models, Journal of the Royal Statistical Society. Series C (Applied ...

A solid coverage of the most important parts of the theory and application of regression models, and generalised linear models. Multiple regression and regression diagnostics. Generalised linear ...