Paper 1, Section II, J

Applied Probability
Part II, 2018

Let λ:[0,)(0,)\lambda:[0, \infty) \rightarrow(0, \infty) be a continuous function. Explain what is meant by an inhomogeneous Poisson process with intensity function λ\lambda.

Let (Nt:t0)\left(N_{t}: t \geqslant 0\right) be such an inhomogeneous Poisson process, and let Mt=Ng(t)M_{t}=N_{g(t)} where g:[0,)[0,)g:[0, \infty) \rightarrow[0, \infty) is strictly increasing, differentiable and satisfies g(0)=0g(0)=0. Show that MM is a homogeneous Poisson process with intensity 1 if Λ(g(t))=t\Lambda(g(t))=t for all tt, where Λ(t)=0tλ(u)du\Lambda(t)=\int_{0}^{t} \lambda(u) d u. Deduce that NtN_{t} has the Poisson distribution with mean Λ(t)\Lambda(t).

Bicycles arrive at the start of a long road in the manner of a Poisson process N=(Nt:t0)N=\left(N_{t}: t \geqslant 0\right) with constant intensity λ\lambda. The ii th bicycle has constant velocity ViV_{i}, where V1,V2,V_{1}, V_{2}, \ldots are independent, identically distributed random variables, which are independent of NN. Cyclists can overtake one another freely. Show that the number of bicycles on the first xx miles of the road at time tt has the Poisson distribution with parameter λE(V1min{x,Vt})\lambda \mathbb{E}\left(V^{-1} \min \{x, V t\}\right).