Linear regression (also called simple regression) is one of the most common techniques of regression analysis. Multiple regression is a broader class of regression analysis, which encompasses both ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...

The topic of variable importance in linear regression is reviewed, and a measure first justified theoretically by Pratt (1987) is examined in detail. Asymptotic variance estimates are used to ...

We propose a multivariate sparse group lasso variable selection and estimation method for data with highdimensional predictors as well as high-dimensional response variables. The method is carried out ...