Functions to calculate the coefficient(s) of the robust linear regression model from a bootstrapped sample

1 2 3 4 5 6 7 | ```
bootStatResiduals(residData, inds, coefind, intercept = TRUE, maxTries = 4L)
bootStatCases(origData, inds, coefind, formula, maxTries = 4L)
bootStatFastControl(model)
bootStatFast(origData, inds, control, coefind)
``` |

`residData` |
the original data set with the columns fit, resid and the predictor variables instead of the response variable. |

`inds` |
the resampled indices. |

`coefind` |
the index of the coefficient to extract. |

`intercept` |
if the model includes an intercept term. |

`maxTries` |
the maximum number of tries to increase the maxit control arguments for the S estimator. |

`origData` |
the original data set. |

`formula` |
the formula to fit the model |

`model` |
The lmrob model |

`control` |
the control object as returned by |

Different approaches for bootstrapping have been implemented. The default "fast and robust bootstrap"
(FRB) proposed by M. Salibian-Barrera, et al. (2002), implemented with `bootStatFast`

is the
fastest and most resistant to outliers, while the other two `bootStatResiduals`

and `bootStatCases`

are standard bootstrap methods, where the residuals resp. the cases are resampled and the model is
fit to this data.

M. Salibian-Barrera, S. Aelst, and G. Willems. Fast and robust bootstrap. Statistical Methods and Applications, 17(1):41-71, 2008.

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