Description Usage Arguments Details Value Source Examples

Function to cross-validate a high dimensional Cox survival model using Univariate Shrinkage

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`fit` |
object returned by call to uniCox |

`x` |
Feature matrix, n obs by p variables |

`y` |
Vector of n survival times |

`status` |
Vector of n censoring indicators (1= died or event occurred, 0=survived, or event was censored) |

`nfolds` |
Number of cross-valdiation folds |

`folds` |
Optional list of sample numbers defining folds |

This function does cross-validation for a prediction model for survival data with high-dimensional covariates, using the Unvariate Shringae method.

A list with components

`devcvm` |
Average drop in CV deviance for each lambda value |

`ncallcvm=ncallcvm` |
Average number of features with non-zero wts in the CV, for each lambda value |

`se.devcvm` |
Standard error of average drop in CV deviance for each lambda value |

`devcv` |
Drop in CV deviance for each lambda value |

`ncallcv` |
Number of features with non-zero wts in the CV, for each lambda value |

`folds` |
Indices for CV folds |

`call` |
Call to this function |

Tibshirani, R. Univariate shrinkage in the Cox model for high dimensional data (2009). http://www-stat.stanford.edu/~tibs/ftp/cus.pdf To appear SAGMB.

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