Naive Bayes regression is essentially a variation of basic linear regression. In simple linear regression, there is a single predictor variable x, and a single target variable y to predict. For ...

Before building my model, I want to step back to offer an easy-to-understand definition of linear regression and why it’s vital to analyzing data. What is linear regression?

Below is an example for unknown nonlinear relationship between age and log wage and some different types of parametric and nonparametric regression lines. One can see that nonparametric regressions ...

Linear forecasting models can be used in both types of forecasting methods. In the case of causal methods, the causal model may consist of a linear regression with several explanatory variables.

Several years ago, Spurrier considered the multiple comparison of several simple linear regression lines. He constructed simultaneous confidence bands for all of the contrasts of the simple linear ...

Model-combining (i.e., mixing) methods have been proposed in recent years to deal with uncertainty in model selection. Even though advantages of model combining over model selection have been ...

In this way, a GWAS with simple linear regression is performed 50–60 times faster than with standard implementations.