normDiff: Similarity metric of normalized difference

In BaderLab/netDx: Network-based patient classifier

Description

Similarity metric of normalized difference

Usage

normDiff(x)

Arguments

x	(numeric) vector of values, one per patient (e.g. ages)

Details

Similarity metric used when data for a network consists of exactly 1 continuous variable (e.g. a network based only on 'age'). When number of variables is 2-5, use avgNormDiff() which takes the average of normalized difference for individual variables

Value

symmetric matrix of size ncol(dat) (number of patients) containing pairwise patient similarities

Examples

sim <- normDiff(rnorm(10))

BaderLab/netDx documentation built on Sept. 26, 2021, 9:13 a.m.