Calculate the entropy of a set of predictions and estimate 95% confidence intervals.

entropy_bs_ci.r

# Libraries
library(gmish) # devtools::install_github('gweissman/gmish')

# Size
N <- 1000

# Softmax helper function
sm <- function(x) exp(x)/sum(exp(x))

# Make some predictions
preds <- data.frame(runif(N), runif(N), runif(N))
preds_sm <- t(apply(preds, 1, sm))

# Calculate entropy
ent(preds_sm)

# Get bias-corrected, accelerated bootstrap confidence intervals
bs_ci(preds_sm, metric = ent, btype = 'bca')