在 R 中绘制蒙特卡罗模拟

Question

I am trying to create a plot that graph a Monte Carlo simulation of a coin toss with iterations on x and probability on y. However, I am having difficulty creating the necessary function.

So far I have

set.seed(2738952)
coins<-function(n){
    sample(c(0,1),n,replace=TRUE)
}
mean(coins(10000)==1)

ggplot(mapping = aes(x=iteration,y=coins))+geom_line()

Error: Aesthetics must be valid data columns. Problematic aesthetic(s): y = coins. Did you mistype the name of a data column or forget to add stat()?

I am unsure how to create the iterations as well as the probability.

Answer 1

Is this something you're looking for?

iterations <- 100
flip_results <- coins(iterations)
# As @teunbrand suggested, use cumsum to avoid looping
pct_head <- pct_head <- cumsum(flip_results) / seq_len(iterations)
ggplot(mapping = aes(x=1:iterations,y=pct_head))+geom_line()