calf: calf

In CALF: Coarse Approximation Linear Function

calf

Description

Coarse Approximation Linear Function

Usage

calf(data, nMarkers, targetVector, 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 = "nonbinary"). 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 "nonbinary" for target vector with real numbers.
optimize	Criteria to optimize, "pval" or "auc", (if targetVector = "binary") or "corr" (if targetVector = "nonbinary"). Defaults to "pval".
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.

If targetVector is binary, rocPlot. A plot object from ggplot2 for the receiver operating curve.

Examples

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

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