calf_randomize: calf_randomize

In CALF: Coarse Approximation Linear Function

calf_randomize

Description

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

Usage

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

Arguments

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.

Value

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.

Examples

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

CALF documentation built on March 18, 2022, 5:35 p.m.