Description Usage Arguments Details Value Author(s) See Also

This function bootstraps the model *n* times to estimate for each variable the empirical bootstrapped distribution of model coefficients, and net residual improvement (NeRI).
At each bootstrap the non-observed data is predicted by the trained model, and statistics of the test prediction are stores and reported.

1 2 3 4 5 6 7 8 |

`fraction` |
The fraction of data (sampled with replacement) to be used as train |

`loops` |
The number of bootstrap loops |

`model.formula` |
An object of class |

`Outcome` |
The name of the column in |

`data` |
A data frame where all variables are stored in different columns |

`type` |
Fit type: Logistic ("LOGIT"), linear ("LM"), or Cox proportional hazards ("COX") |

`plots` |
Logical. If |

`bestmodel.formula` |
An object of class |

The bootstrap validation will estimate the confidence interval of the model coefficients and the NeRI.
It will also compute the train and blind test root-mean-square error (RMSE), as well as the distribution of the NeRI *p*-values.

`data` |
The data frame used to bootstrap and validate the model |

`outcome` |
A vector with the predictions made by the model |

`boot.model` |
An object of class |

`NeRIs` |
A matrix with the NeRI for each model term, estimated using the bootstrap test sets |

`tStudent.pvalues` |
A matrix with the |

`wilcox.pvalues` |
A matrix with the Wilcoxon rank-sum test |

`bin.pvalues` |
A matrix with the binomial test |

`F.pvalues` |
A matrix with the |

`test.tStudent.pvalues` |
A matrix with the |

`test.wilcox.pvalues` |
A matrix with the Wilcoxon rank-sum test |

`test.bin.pvalues` |
A matrix with the binomial test |

`test.F.pvalues` |
A matrix with the |

`testPrediction` |
A vector that contains all the individual predictions used to validate the model in the bootstrap test sets |

`testOutcome` |
A vector that contains all the individual outcomes used to validate the model in the bootstrap test sets |

`testResiduals` |
A vector that contains all the residuals used to validate the model in the bootstrap test sets |

`trainPrediction` |
A vector that contains all the individual predictions used to validate the model in the bootstrap train sets |

`trainOutcome` |
A vector that contains all the individual outcomes used to validate the model in the bootstrap train sets |

`trainResiduals` |
A vector that contains all the residuals used to validate the model in the bootstrap train sets |

`testRMSE` |
The global RMSE, estimated using the bootstrap test sets |

`trainRMSE` |
The global RMSE, estimated using the bootstrap train sets |

`trainSampleRMSE` |
A vector with the RMSEs in the bootstrap train sets |

`testSampledRMSE` |
A vector with the RMSEs in the bootstrap test sets |

Jose G. Tamez-Pena and Antonio Martinez-Torteya

```
bootstrapValidation_Bin,
plot.bootstrapValidation_Res
```

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