Here's what I have:
Let X be a simple birth-death process where individuals have independent $\text{Exp}(\mu)$ lifetimes and, during their lifetime give birth at rate $λ$ independently of other individuals.
Let $T = \inf\{t ≥ 0: X_{t} = 0\}$ be the extinction time for the population.
I have to find the density of T.
Earlier in the question I had to show that if $G(s, t) = E(s^{X_{t}})$, then $G$ satisfies :
$$ \frac{∂}{∂t}G(s, t) = (λs − \mu)(s − 1) \frac{∂}{∂s}G(s, t)$$
which I did.
The hint is that the solution to the above is given by:
$$\frac{\mu(s − 1) − (\lambda s − \mu)e^{-(\lambda-\mu)t}}{\lambda(s − 1) − (\lambda s − \mu)e^{-(\lambda-\mu)t}} $$ or
$$\frac{\lambda t(s-1)-s}{\lambda t(s-1)-1}$$
depending on whether $\mu \neq \lambda$ or $\mu = \lambda$.
Another observation is that $G(0, t) = P(X_t = 0)$ and that $$\inf\{t ≥ 0: X_{t} = 0\} \leq k \Leftrightarrow X_k=0$$
I just can add all those things up to a solution.
Any help is appreciated
Note that $G(s,t) = E[s^{X_t}]$ is the probability generating function of $X_t$. Therefore, $$P(X_t = k) = \frac{d^kG(s,t)}{ds^k}(0,t)$$ As a special case, $G(0,t)=P(X_t=0)$.
Next, the hint tells you that $P(T \leq t) = P(X_t=0)$. Can yo you use the previous item to determine $P(T \leq t)$?
Finally, use $$f_{T}(t)=\frac{dP(T \leq t)}{dt}$$