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MAS328 Solutions to the final exam. Question 1. (20 marks) Four ...

MAS328 Solutions to the final exam. Question 1. (20 marks) Four ...

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<strong>Solutions</strong> <strong>to</strong> <strong>the</strong> <strong>final</strong> <strong>exam</strong>.<br />

<strong>MAS328</strong><br />

<strong>Question</strong> <strong>1.</strong> (<strong>20</strong> <strong>marks</strong>)<br />

<strong>Four</strong> players A, B, C, D are connected by <strong>the</strong> following network, and play by<br />

exchanging one <strong>to</strong>ken.<br />

D<br />

A B C<br />

At each step of <strong>the</strong> game, <strong>the</strong> player who holds <strong>the</strong> <strong>to</strong>ken chooses ano<strong>the</strong>r<br />

player he is connected <strong>to</strong>, and sends <strong>the</strong> <strong>to</strong>ken <strong>to</strong> that player.<br />

(i) Assuming that player choices are made at random and equally distributed,<br />

model <strong>the</strong> states of <strong>the</strong> <strong>to</strong>ken as a Markov chain and give its<br />

transition matrix.<br />

The transition matrix P is given by<br />

⎡<br />

0<br />

⎢<br />

P = ⎢ 1/3<br />

⎣ 0<br />

1/2<br />

0<br />

1<br />

0<br />

1/3<br />

0<br />

⎤<br />

1/2<br />

1/3 ⎥<br />

0 ⎦<br />

1/2 1/2 0 0<br />

.<br />

(ii) Compute <strong>the</strong> stationary distribution (πA, πB, πC, πD) of (Xn)n≥<strong>1.</strong><br />

Hint: To simplify <strong>the</strong> resolution, start by arguing that we have πA = πD.<br />

Solving for πP = π we have<br />

πP =<br />

⎡<br />

0<br />

⎢<br />

[πA, πB, πC, πD] ⎢ 1/3<br />

⎣ 0<br />

1/2<br />

0<br />

1<br />

0<br />

1/3<br />

0<br />

⎤<br />

1/2<br />

1/3 ⎥<br />

0 ⎦<br />

1/2 1/2 0 0<br />

=<br />

⎡<br />

⎢<br />

⎣<br />

= [πA, πB, πC, πD],<br />

1<br />

1<br />

3πB + 1<br />

2πD 1<br />

2πA + πC + 1<br />

2πD 1<br />

3πB 1<br />

2πA + 1<br />

3πB ⎤<br />

⎥<br />


<strong>MAS328</strong><br />

i.e. πA = πD = 2πC and πB = 3πC, which, under <strong>the</strong> condition πA +<br />

πB + πC + πD = 1, gives πA = 1/4, πB = 3/8, πC = 1/8, πD = 1/4.<br />

(iii) In <strong>the</strong> long run, what is <strong>the</strong> probability that player D holds <strong>the</strong> <strong>to</strong>ken ?<br />

This probability is πD = 0.25.<br />

(iv) On average, how long does player D has <strong>to</strong> wait <strong>to</strong> recover <strong>the</strong> <strong>to</strong>ken ?<br />

This average time is 1/πD = 4.<br />

<strong>Question</strong> 2. (<strong>20</strong> <strong>marks</strong>)<br />

A system consists of two machines and two repairmen. The amount of time<br />

that an operating machine works before breaking down is exponentially distributed<br />

with mean 5. The amount it takes a single repairman <strong>to</strong> fix a<br />

machine is exponentially distributed with mean 4. Only one repairman can<br />

work on a failed machine at any given time.<br />

(i) Let Xt be <strong>the</strong> number of machines in operating condition at time t ∈<br />

R+. Show that Xt is a continuous time Markov process and complete<br />

<strong>the</strong> missing entries in <strong>the</strong> matrix<br />

of its genera<strong>to</strong>r.<br />

⎡<br />

Q = ⎣<br />

0.5 0<br />

0.2 <br />

0 −0.4<br />

The genera<strong>to</strong>r Q of Xt is given by<br />

⎡<br />

−0.5 0.5 0<br />

⎤<br />

Q = ⎣ 0.2 −0.45 0.25 ⎦ .<br />

0 0.4 −0.4<br />

2<br />

⎤<br />


(ii) Calculate <strong>the</strong> long run probability distribution (π0, π1, π2) for Xt.<br />

Solving for πQ = 0 we have<br />

⎡<br />

πQ = [π0, π1, π2] ⎣<br />

⎡<br />

−0.5 0.5 0<br />

0.2 −0.45 0.25<br />

0 0.4 −0.4<br />

= ⎣<br />

−0.5 × π0 + 0.2 × π1<br />

0.5 × π0 − 0.45 × π1 + 0.4 × π2<br />

0.25 × π1 − 0.4 × π2<br />

= [0, 0, 0],<br />

⎤<br />

⎦<br />

⎤<br />

⎦<br />

T<br />

<strong>MAS328</strong><br />

i.e. π0 = 0.4 × π1 = 0.64 × π2 under <strong>the</strong> condition π0 + π1 + π2 = 1,<br />

which gives π0 = 16/81, π1 = 40/81, π2 = 25/8<strong>1.</strong><br />

(iii) Compute <strong>the</strong> average number of operating machines in <strong>the</strong> long run.<br />

In <strong>the</strong> long run <strong>the</strong> average is<br />

0 × π0 + 1 × π1 + 2 × π2 = 40/81 + 50/81 = 90/8<strong>1.</strong><br />

(iv) If an operating machine produces 100 units of output per hour, what<br />

is <strong>the</strong> long run output per hour of <strong>the</strong> system ?<br />

We find<br />

100 × 90/81 = 1000/9.<br />

<strong>Question</strong> 3. (<strong>20</strong> <strong>marks</strong>)<br />

Families in a distant society continue <strong>to</strong> have children until <strong>the</strong> first girl, and<br />

<strong>the</strong>n cease childbearing. Let X denote <strong>the</strong> number of male offsprings of a<br />

particular husband.<br />

(i) Assuming that each child is equally likely <strong>to</strong> be a boy or a girl, give <strong>the</strong><br />

probability distribution of X.<br />

We have P(X = k) = (1/2) k+1 , k ∈ N.<br />

3


(ii) Compute <strong>the</strong> probability generating function G(s) of X.<br />

The probability generating function of X is given by<br />

G(s) = E[s X ] = 1<br />

2<br />

∞<br />

k=0<br />

(s/2) k = 1<br />

2 − s .<br />

<strong>MAS328</strong><br />

(iii) What is <strong>the</strong> probability that <strong>the</strong> husband’s male line of descent will<br />

cease <strong>to</strong> exist by <strong>the</strong> third generation ?<br />

The probability we are looking for is<br />

G(G(G(0))) =<br />

1<br />

2 − 1<br />

2−1/2<br />

= 3<br />

4 .<br />

<strong>Question</strong> 4. (<strong>20</strong> <strong>marks</strong>)<br />

Suppose that X(A) is a spatial Poisson process of discrete items scattered<br />

on <strong>the</strong> plane R 2 with intensity λ = 0.5 per square meter. No evaluation of<br />

numerical expressions is required in this question.<br />

(i) What is <strong>the</strong> probability that 10 items are found within <strong>the</strong> disk D(0, 3)<br />

with radius 3 meters centered at <strong>the</strong> origin ?<br />

This probability is<br />

−9π/2 (9π/2)10<br />

e .<br />

10!<br />

(ii) What is <strong>the</strong> probability that 5 items are found within <strong>the</strong> disk D(0, 3)<br />

and 3 items are found within <strong>the</strong> disk D(x, 3) with x = (7, 0) ?<br />

This probability is<br />

−9π/2 (9π/2)5<br />

e<br />

5!<br />

4<br />

(9π/2)3<br />

× e−9π/2 .<br />

3!


<strong>MAS328</strong><br />

(iii) What is <strong>the</strong> probability that 8 items are found anywhere within D(0, 3)∪<br />

D(x, 3) with x = (7, 0) ?<br />

This probability is<br />

−9π (9π)8<br />

e .<br />

8!<br />

<strong>Question</strong> 5. (<strong>20</strong> <strong>marks</strong>)<br />

Let (ξn)n≥0 be a two-state Markov chain on {0, 1} with transition matrix<br />

<br />

0<br />

1 − α<br />

<br />

1<br />

,<br />

α<br />

let (Nt)t∈R+ be a Poisson process with parameter λ > 0, and let <strong>the</strong> two-state<br />

birth and death process Xt be defined by<br />

Xt = ξNt, t ∈ R+.<br />

(i) Compute <strong>the</strong> mean return time E[τ0 | X0 = 0] <strong>to</strong> 0 of Xt.<br />

We have<br />

and<br />

hence<br />

and<br />

E[τ0 | X0 = 0] = 1<br />

λ + E[τ0 | X0 = 1],<br />

E[τ0 | X0 = 1] = 1<br />

λ + αE[τ0 | X0 = 1],<br />

E[τ0 | X0 = 1] =<br />

E[τ0 | X0 = 0] =<br />

5<br />

1<br />

λ(1 − α)<br />

2 − α<br />

λ(1 − α) .


(ii) Compute <strong>the</strong> mean return time E[τ1 | X0 = 1] <strong>to</strong> 1 of Xt.<br />

We have<br />

<strong>MAS328</strong><br />

E[τ1 | X0 = 1] = 1<br />

λ + αE[τ1 | X0 = 1] + (1 − α)E[τ1 | X0 = 0]<br />

= 2 − α<br />

λ + αE[τ1 | X0 = 1],<br />

since E[τ1 | X0 = 0] = 1/λ, hence<br />

E[τ1 | X0 = 1] =<br />

2 − α<br />

λ(1 − α) .<br />

(iii) Determine <strong>the</strong> genera<strong>to</strong>r of <strong>the</strong> process Xt in terms of α and λ.<br />

The genera<strong>to</strong>r Q of Xt is given by<br />

<br />

−λ λ<br />

Q =<br />

λ(1 − α) −λ(1 − α)<br />

6<br />

<br />

.

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