Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

Generalized Linear Models and Categorical Data Analysis in R Course Topics Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an ...

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 ...

We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

Zheng Yuan, Yuhong Yang, Combining Linear Regression Models: When and How?, Journal of the American Statistical Association, Vol. 100, No. 472 (Dec., 2005), pp. 1202-1214 ...