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 ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

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 ...

This section illustrates how to solve some ordinary least-squares problems and generalizations of those problems by formulating them as transformation regression problems. One problem involves finding ...

This is a preview. Log in through your library . Abstract A Bayesian decision theory approach to the choice of regression design is considered when it is intended to use the regression to help control ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...