inst/code/pois_vs_binom.R

In stephenslab/fastTopics: Fast Algorithms for Fitting Topic Models and Non-Negative Matrix Factorizations to Count Data

# Small script to illustrate the Poisson approximation to the binomial
# likelihood.

# Simulate binomial data.
set.seed(1)
n <- 1000
p <- 0.1
x <- rbinom(1,n,p)

# Plot binomial and Poisson likelihoods.
p  <- seq(0,0.25,length.out = 1000)
f1 <- dbinom(x,n,p,log = TRUE)
f2 <- dpois(x,n*p,log = TRUE)
f1 <- exp(f1 - max(f1))
f2 <- exp(f2 - max(f2))
f1 <- f1/sum(f1)
f2 <- f2/sum(f2)
plot(p,f1,type = "l",col = "darkorange",lwd = 2)
lines(p,f2,col = "darkblue",lwd = 2,lty = "dashed")