Description Usage Arguments Value

This is an implementation of a simple algorithm that selects the 'best' variables as the predictors in a linear regression model. The selection is based on choosing the variables that give the highest adjusted R-squared value.

1 | ```
var_select(data, y, stopat = Inf)
``` |

`data` |
A data frame containing the predictor variables (X) and the dependent variable (Y). |

`y` |
The name of the dependent variable. |

`stopat` |
The total number of variables to include in the model.
Default is |

A nested tibble with the lm models and stats.

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