calf_exact_binary_subset {CALF} | R Documentation |

## calf_exact_binary_subset

### Description

Runs Coarse Approximation Linear Function on a random subset of binary data provided, with the ability to precisely control the number of case and control data used.

### Usage

```
calf_exact_binary_subset(
data,
nMarkers,
nCase,
nControl,
times = 1,
optimize = "pval",
verbose = FALSE
)
```

### Arguments

`data` |
Matrix or data frame. First column must contain case/control dummy coded variable. |

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

`nCase` |
Numeric. A value indicating the number of case data to use. |

`nControl` |
Numeric. A value indicating the number of control data to use. |

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

`optimize` |
Criteria to optimize. 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. |

### Value

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

The optimal AUC or pval for the classification. If multiple replications are requested, a data.frame containing all optimized values across all replications is returned.

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

### Examples

```
calf_exact_binary_subset(data = CaseControl, nMarkers = 6, nCase = 5, nControl = 8, times = 5)
```

*CALF*version 1.0.17 Index]