Description Usage Arguments Details Value Author(s) References See Also Examples

This function builds a prediction rule based on the learning data (clinical predictors only)
and applies it to the test data. It uses the function `cforest`

from the package `party`

. See Boulesteix et al (2008) for more details.

1 |

`Xlearn` |
A nlearn x p matrix giving the microarray predictors for the learning data set. This argument is ignored. |

`Zlearn` |
A nlearn x q matrix giving the clinical predictors for the learning data set. |

`Ylearn` |
A numeric vector of length nlearn giving the class membership of the learning observations, coded as 0,...,K-1 (where K is the number of classes). |

`Xtest` |
A ntest x p matrix giving the microarray predictors for the test data set. This argument is ignored. |

`Ztest` |
A ntest x q matrix giving the clinical predictors for the test data set. |

`...` |
Other arguments to be passed to the function |

See Boulesteix et al (2008).

A list with the elements:

`prediction` |
A numeric vector of length |

`importance` |
The variable importance information output
by the function |

`OOB` |
The out-of-bag error of the constructed forest. |

Anne-Laure Boulesteix (http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/020_professuren/boulesteix/)

Boulesteix AL, Porzelius C, Daumer M, 2008. Microarray-based classification and clinical predictors: On combined classifiers and additional predictive value. Bioinformatics 24:1698-1706.

`testclass`

, `testclass_simul`

, `simulate`

,
`plsrf_x_pv`

, `plsrf_xz_pv`

, `plsrf_x`

, `plsrf_xz`

,
`logistic_z`

, `svm_x`

.

1 2 3 4 5 6 7 8 9 10 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.