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 ...

The joint-regression model for two-way data assumes a linear relation between a continuous response and column effects. Standard methods for fitting the model condition on estimates of the column ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Olaf Bunke, Bernd Droge, Bootstrap and Cross-Validation Estimates of the Prediction Error for Linear Regression Models, The Annals of Statistics, Vol. 12, No. 4 (Dec ...

R 2 (R-squared) is a statistical measure of the goodness of fit of a linear regression model (from 0.00 to 1.00), also known as the coefficient of determination.

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

The second commands means, "Predict the value of the dependent variable (Income) using the information in the linear regression model named model and input values supplied by the data frame named mydf ...