Handout on a Critical Branching Process
Problem. Consider a branching process with the following
probabilities: pj=P(N1=j)=(½)j+1, j=0,1,2,.... Find the probability ej that
the process dies out by generation j, and also find the distribution of Nj.
Compute the conditional istribution of Nj conditioned on the event {Nj > 0}, and
find the conditional expected number of members of generation j, that is E(Nj | Nj > 0).
Solution
First, note that this is a critical
branching process - compute the average number of particles
Hence the process must eventually die out.
Next, observe that
G(s)=1/2 + 1/4 s+1/8 s2+1/16 s3+ .... = 1/2 (
1+ [s/2] +1/8 [s/2]2+1/16 [s/2]3+....=1/2
(1-s/2)-1=1/(2-s)
Therefore,
G2(s)=G(G(s))=(2-s)/(3-2s)
G3(s)=G(G(G(s)))=(3-2s)/(4-3s)
and so on - by induction it is easy to show that
Gj(s)=[j-(j-1)s] / [(j+1)-js]
Hence
jGj(s)-(j-1)
= (j+1-js)-1 = (j+1)-1 (1 - rjs)-1
= [1+(rjs)+(rjs)2+(rjs)3+...] / (j+1)
where
rj=j/(j+1)
Therefore,
Gj(s)=[j2+
(rjs)+(rjs)2+(rjs)3+... ] / (j+j2)
Now we can "decode" the p.m.f. of Nj using the p.g.f. Namely:
ej = P(Nj=0)=j2
/ (j+j2) = j / (j+1)
which approaches 1.
Moreover,
P(Nj=1)=(rj) / (j+j2)
P(Nj=2)=(rj)2 / (j+j2)
and so on, thus
giving
P(Nj=k)=(rj)k / (j+j2)
for k=1,2,3,....
Finally, since
1 - P(Nj=0) = sum ( P(Nj=k), k=1,2,3,... ) = sum ( (rj)k / (j+j2)
, k=1,2,3,...)
=1 / (j+j2) × 1 / (1-rj)
= 1 / (j+1)
we have
P(Nj=k
| Nj>0 )=(rj)k
/ (j+j2) / P(Nj>0) = (rj)k / j
for k=1,2,3,.... and
hence
E (Nj=k
| Nj>0 )
= sum ( P(Nj=k
| Nj>0 ) × k , k=1,2,3,...) = sum ( k (rj)k
/ j , k=1,2,3,...)
= j+1
Thus the conditional (given survival) expected number of particles goes to
infinity!
Note: useful formula:
sum ( ak × k , k=1,2,3,...)
= a sum ( ak-1 × k , k=1,2,3,...) = a sum ( ak , k=1,2,3,...)'
=
= a sum ( ak , k=0,1,2,3,...)'
= a ( (1-a)-1 )' = a / (1-a)2