1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
|
###################################################
# Section 4.3 A Multinomial Model
###################################################
library(LearnBayes)
alpha = c(728, 584, 138)
theta = rdirichlet(1000, alpha)
hist(theta[, 1] - theta[, 2], main="")
S=readline(prompt="Type <Return> to continue : ")
###########################################
data(election.2008)
attach(election.2008)
prob.Obama=function(j)
{
p=rdirichlet(5000,
500*c(M.pct[j],O.pct[j],100-M.pct[j]-O.pct[j])/100+1)
mean(p[,2]>p[,1])
}
Obama.win.probs=sapply(1:51,prob.Obama)
sim.election=function()
{
winner=rbinom(51,1,Obama.win.probs)
sum(EV*winner)
}
sim.EV=replicate(1000,sim.election())
windows()
hist(sim.EV,min(sim.EV):max(sim.EV),col="blue")
abline(v=365,lwd=3) # Obama received 365 votes
text(375,30,"Actual \n Obama \n total")
|
