A2.1

Markov Chains
Part II, 2001

(i) The fire alarm in Mill Lane is set off at random times. The probability of an alarm during the time-interval (u,u+h)(u, u+h) is λ(u)h+o(h)\lambda(u) h+o(h) where the 'intensity function' λ(u)\lambda(u) may vary with the time uu. Let N(t)N(t) be the number of alarms by time tt, and set N(0)=0N(0)=0. Show, subject to reasonable extra assumptions to be stated clearly, that pi(t)=P(N(t)=i)p_{i}(t)=P(N(t)=i) satisfies

p0(t)=λ(t)p0(t),pi(t)=λ(t){pi1(t)pi(t)},i1.p_{0}^{\prime}(t)=-\lambda(t) p_{0}(t), \quad p_{i}^{\prime}(t)=\lambda(t)\left\{p_{i-1}(t)-p_{i}(t)\right\}, \quad i \geqslant 1 .

Deduce that N(t)N(t) has the Poisson distribution with parameter Λ(t)=0tλ(u)du\Lambda(t)=\int_{0}^{t} \lambda(u) d u.

(ii) The fire alarm in Clarkson Road is different. The number M(t)M(t) of alarms by time tt is such that

P(M(t+h)=m+1M(t)=m)=λmh+o(h),P(M(t+h)=m+1 \mid M(t)=m)=\lambda_{m} h+o(h),

where λm=αm+β,m0\lambda_{m}=\alpha m+\beta, m \geqslant 0, and α,β>0\alpha, \beta>0. Show, subject to suitable extra conditions, that pm(t)=P(M(t)=m)p_{m}(t)=P(M(t)=m) satisfies a set of differential-difference equations to be specified. Deduce without solving these equations in their entirety that M(t)M(t) has mean β(eαt1)/α\beta\left(e^{\alpha t}-1\right) / \alpha, and find the variance of M(t)M(t).