calf_randomize {CALF} | R Documentation |

Randomly selects from binary input provided to data parameter and runs Coarse Approximation Linear Function.

```
calf_randomize(
data,
nMarkers,
targetVector,
times = 1,
optimize = "pval",
verbose = FALSE
)
```

`data` |
Matrix or data frame. Must be binary data such that the first column must contain case/control dummy coded variable, as function is only approprite for binary data. |

`nMarkers` |
Maximum number of markers to include in creation of sum. |

`targetVector` |
Indicate "binary" for target vector with two options (e.g., case/control). Indicate "nonbinary" for target vector with real numbers. |

`times` |
Numeric. Indicates the number of replications to run with randomization. |

`optimize` |
Criteria to optimize if targetVector = "binary." Indicate "pval" to optimize the p-value corresponding to the t-test distinguishing case and control. Indicate "auc" to optimize the AUC. |

`verbose` |
Logical. Indicate TRUE to print activity at each iteration to console. Defaults to FALSE. |

A data frame containing the chosen markers and their assigned weight (-1 or 1)

The optimal AUC, pval, or correlation for the classification.

aucHist A histogram of the AUCs across replications, if applicable.

```
calf_randomize(data = CaseControl, nMarkers = 6, targetVector = "binary", times = 5)
```

[Package *CALF* version 1.0.17 Index]