hpb: H+ discordance estimation with bootstrapping

In fasthplus: Fast Label-Dissimilarity Discordance Estimation with H+

Description

Estimates the H+ discordance metric given data Dat and a label vector L. Bootstrapping is performed over r iterations with s points sampled per iterate.

Usage

hpb(D, L, r = 30, t)

Arguments

D	numeric matrix or data frame with observations in rows (nxm)
L	numeric vector containing a set of length n
r	numeric number of bootstrap iterations
t	numeric pre-bootstrap sample size, 1-5% of n

Value

list, h is the estimated H+ value.

gamma1 and gamma2 are plausible ranges for what % of A (or Dw)

are strictly greater than B (or Db)

Examples

a <- sapply(1:500, function(i) rnorm(n=50, mean=0))
b <- sapply(1:500, function(i) rnorm(n=50, mean=0))
x <- t(cbind(a,b))
l <- c(rep(0,500), rep(1,500))
h <- hpb(D=x, L=l, r=30,t=50)

fasthplus documentation built on Feb. 7, 2022, 5:16 p.m.