entropy.weight: Maximum entropy weights

In mdw: Maximum Diversity Weighting

Description

entropy.weight produces a set of weights that maximizes the total weighted entropy of the distribution of different biomarkers within each subject, values of biomarkers can be either continuous or categorical.

Usage

entropy.weight(X, h)

Arguments

X	n by p maxtrix containing observations of p biomarkers of n subjects.
h	bandwidth for kernel density estimation. if data is categorical, set to 'na'.

Examples

library(MASS)
# a three biomarkers dataset generated from independent normal(0,1)
set.seed(1)
X = mvrnorm(n = 100, mu=rep(0,3), Sigma=diag(3), tol = 1e-6, empirical = FALSE, EISPACK = FALSE)
entropy.weight(X, h=1)
###
# a three categorical biomarkers dataset
set.seed(1)
tmp=mvrnorm(n=10,mu=c(0,0,0),Sigma = diag(3))
dat=t(apply(tmp, 1, function(x) cut(x,c(-Inf,-0.5,0.5,Inf),labels=1:3)))
entropy.weight(dat,h='na')

Example output

[1] 0.3518879 0.3436133 0.3044988
[1] 0.4080125 0.1840237 0.4079638

mdw documentation built on July 1, 2020, 10:27 p.m.