calf: calf

In stlane/calf: Coarse Approximation Linear Function

Description

Coarse approximation linear function

Usage

calf(data, nMarkers, targetVector, margin, optimize = "pval",
  verbose = FALSE)

Arguments

data	Matrix or data frame. First column must contain case/control dummy coded variable (if targetVector = "binary"). Otherwise, first column must contain real number vector corresponding to selection variable (if targetVector = "real"). All other columns contain relevant markers.
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 "real" for target vector with real numbers.
margin	Real number from 0 to 1. Indicates the amount a potential marker must improve the target criterion (Pearson correlation or p-value) in order to add the marker.
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 AUC value for the classification

rocPlot. A plot object from ggplot2 for the receiver operating curve.

Examples

calf(data = CaseControl, nMarkers = 6, targetVector = "binary")

stlane/calf documentation built on May 30, 2019, 5:48 p.m.