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 ...

Stepwise Regression So, here you are, with a plethora of potential independent variables arrayed before you. There is no substitute for the use of good judgment in choosing which to include in your ...

Subsequently, the team constructed metabolite content conversion models for 101 key metabolites using stepwise multiple regression, achieving high accuracy (R² > 0.9).