entropy.weight {mdw} | R Documentation |
Maximum entropy weights
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')
[Package mdw version 2020.6-17 Index]