Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Objectives: This study aimed to evaluate the effectiveness of value-based care (VBC) interventions in slowing the progression of chronic kidney disease (CKD), as measured by changes in estimated ...

The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

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 ...

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 paper proposes a new approach to modeling heteroskedasticity which enables the modeler to utilize information conveyed by data plots in making informed decisions ...

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 ...