Paper 2, Section II, K

Applied Probability
Part II, 2017

(a) Give the definition of a Poisson process on R+\mathbb{R}_{+}. Let XX be a Poisson process on R+\mathbb{R}_{+}. Show that conditional on {Xt=n}\left\{X_{t}=n\right\}, the jump times J1,,JnJ_{1}, \ldots, J_{n} have joint density function

f(t1,,tn)=n!tn1(0t1tnt)f\left(t_{1}, \ldots, t_{n}\right)=\frac{n !}{t^{n}} \mathbf{1}\left(0 \leqslant t_{1} \leqslant \ldots \leqslant t_{n} \leqslant t\right)

where I(A)\boldsymbol{I}(A) is the indicator of the set AA.

(b) Let NN be a Poisson process on R+\mathbb{R}_{+}with intensity λ\lambda and jump times {Jk}\left\{J_{k}\right\}. If g:R+Rg: \mathbb{R}_{+} \rightarrow \mathbb{R} is a real function, we define for all t>0t>0

R(g)[0,t]={g(Jk):kN,Jkt}\mathcal{R}(g)[0, t]=\left\{g\left(J_{k}\right): k \in \mathbb{N}, J_{k} \leqslant t\right\}

Show that for all t>0t>0 the following is true

P(0R(g)[0,t])=1exp(λ0tI(g(s)=0)ds)\mathbb{P}(0 \in \mathcal{R}(g)[0, t])=1-\exp \left(-\lambda \int_{0}^{t} \mathbf{I}(g(s)=0) d s\right)