Description Usage Arguments Value Author(s) Examples

`stopes`

computes the STOPES estimator.

1 | ```
stopes(x, y, m = 20, prop_split = 0.50, prop_trim = 0.20, q_tail = 0.90)
``` |

`x` |
n x p covariate matrix |

`y` |
n x 1 response vector |

`m` |
number of split samples, with default value = 20 |

`prop_split` |
proportion of data used for training samples, default value = 0.50 |

`prop_trim` |
proportion of trimming, default prop_trim = 0.20 |

`q_tail` |
proportion of truncation samples across the split samples, default values = 0.90 |

`stopes`

returns a list with the STOPE estimates via data splitting using 0.25 method and the PELT method:

`beta_stopes` |
the STOPE estimate via data splitting |

`J_stopes` |
the set of active predictors corresponding to STOPES via data splitting |

`final_cutpoints` |
the final cutpoint for STOPES |

`beta_pelt` |
the STOPE estimate via PELT |

`J_pelt` |
the set of active predictors corresponding to STOPES via PELT |

`final_cutpoints_PELT` |
the final cutpoint for PELT |

`quan_NA` |
test if the vector of trimmed cutpoints has length 0, with 1 if TRUE and 0 otherwise |

Marinela Capanu, Mihai Giurcanu, Colin Begg, and Mithat Gonen

1 2 3 4 5 6 |

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