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 ...

Information for evaluating the statistical significance of stepwise regression models developed with a forward selection procedure is presented. Cumulative distributions of the adjusted coefficient of ...

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

Due to the large number of covariates, researchers used four modeling strategies to identify significant factors: a sequential regression model with variables entered in blocks, a stepwise ...