Monte Carlo Simulation

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1. Set the number of simulations.

NumbSims <- 2e6

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2. Define the variables and their distributions

unifpop <- runif(NumbSims, min=20, max=30)
poispop <- rpois(NumbSims, lambda = 35)
normpop <- rnorm(NumbSims, 15, 4)
tailoredpop <- sample(c(10,10,10,30,30,30,30,30,40), NumbSims, replace = TRUE)

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3. Define the model

combined <- unifpop + poispop + normpop

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4. Explore the results

library(ggplot2)
plt <- ggplot(data.frame(data=c(combined, unifpop, poispop, normpop), labels=rep(c("combined", "unifpop", "poispop", "normpop"), rep(NumbSims,4))), aes(x=data)) +
  stat_bin(aes(fill=labels), position="identity", binwidth=0.25, alpha=0.5) +
  theme_bw()
plt