Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

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 ...

This is a preview. Log in through your library . Abstract Scientists may wish to analyze correlated outcome data with constraints among the responses. For example, piecewise linear regression in a ...