Past exam of the probability course of the University of Oxford / 2015 / 3 / b / iii

The first-step analysis gives $h_0=1$ and, for $k\ge 1$,The minimal nonnegative solution for hitting probabilities theorem states that the probability of ever hitting a target is the pointwise smallest nonnegative solution of this transition recurrence with value one at the target. It follows by comparing any such solution with the probabilities of hitting within $n$ steps, then taking their increasing limit.

The characteristic equation $p{r}^2-r+q=0$ has distinct roots $1$ and $\beta =q/p\in (0,1)$. Hence every solution on the nonnegative integers with boundary value one has the formIf it is nonnegative for all $k$, taking $k\to \infty$ forces $A\ge 0$, and therefore $g_k-{\beta }^k=A(1-{\beta }^k)\ge 0$. The candidate $g_k={\beta }^k$ is itself nonnegative and satisfies the recurrence and boundary value. It is consequently the minimal solution, giving the biased random walk hitting probabilityOn the negative half-line the already established values $h_k=1$ satisfy the same recurrence away from zero. No unproved boundary condition at infinity has been imposed.