9.1.2 Formula notation Given a tibble of data, we have to tell the lm function which column to use as the response variable and which column (or columns, in multiple regression) to use as the ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

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 ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Recent research has focused on l1 penalized least squares (Lasso) estimators for high-dimensional linear regressions in which the number of covariates p is considerably larger than the sample size n.

To infer such associations, researchers often test the structure of the regression coefficients matrix, usually using a likelihood ratio test (LRT). Despite their popularity, classical χ² ...