[This article was first published on R – Xi'an's Og, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. The Riddler of this week has an extinction riddle which summarises as follows:

One observes a population of N individuals, each with a probability of 10⁻⁴ to kill the observer each day. From one day to the next, the population decreases by one individual with probability

K√N 10⁻⁴

What is the value of K that leaves the observer alive with probability ½?

Given the sequence of population sizes N,N¹,N²,…, the probability to remain alive is $(1-10^{-4})^{N+N^1+\ldots}$

where the sum stops with the (sure) extinction of the population. Which is the moment generating function of the sum. At x=1-10⁻⁴. Hence the problem relates to a Galton-Watson extinction problem. However, given the nature of the extinction process I do not see a way to determine the distribution of the sum, except by simulation. Which returns K=26.3 for the specific value of N=9.

```N=9
K=3*N
M=10^4
vals=rep(0,M)
targ=0
ite=1
while (abs(targ-.5)>.01){

for (t in 1:M){
gen=vals[t]=N
while (gen>0){
gen=gen-(runif(1)<K*sqrt(gen)/10^4)
vals[t]=vals[t]+gen}
}
targ=mean(exp(vals*log(.9999)))
print(c(as.integer(ite),K,targ))
if (targ<.5){ K=K*ite/(1+ite)}else{
K=K/(ite/(1+ite))}
ite=ite+1}
```

Filed under: R, Travel Tagged: Francis Galton, Galton-Watson extinction, R, The Riddler  To leave a comment for the author, please follow the link and comment on their blog: R – Xi'an's Og.

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