I tried to solve the following problem:
Buses arrive to an archeological site according to the discrete renewal process with i.i.d inter-arrival times T1, T2, T3, ... which are distributed Geo(p). Assume k−th bus carries a random number Nk of tourists, and that all Nk -s are independent and, for each n = 1, 2, ... the conditional distribution of Nk given Tk+1 = n is U ni{1, ..., n + 2}. According to the archeological site regulations, tourists enter the site immediately upon arrival and leave it as soon as the next bus arrives. Compute the average time (in a long run) that a tourist spends at the site.
I'm pretty sure I'm not fully understanding some concepts and here is the solution that I tried:
First, I noticed that the time each bus stays at the site is the same as the time between buses' arrivals, so I defined the reward as follows: \begin{equation*} R_i = T_{i+1} \end{equation*} Then, I defined the total number of tourists that visit the site as: \begin{equation*} m = \sum_{k=1}^{M(t)} N_k \end{equation*} What I believe I need to calculate is the average time a tourist stays at the site, which is the following ($M(t)$ is the total number of arrivals and $C_T$ the total time needed to for all tourists to visit the site): \begin{equation*} \frac{1}{m}\lim_{t\to\infty} \frac{\sum_{i=1}^{M(t)} R_i}{t} = \frac{1}{m} \lim_{t\to\infty} \frac{C_T}{t} \end{equation*}
My problem is now concluding the solution with the Renewal Reward Theorem. If I didn't have the average ($m$), this would be really straight forward, but given $m$ I'm not sure how to proceed.
RRT:
\begin{equation*} \lim_{t\to\infty} \frac{C_T}{t}\xrightarrow{t\to\infty} \frac{\mathbb{E}(R_i)}{\mathbb{E}(T)} \end{equation*}
I thought I might get the result from RRT and just divide it by $m$. Like this, considering that the renewal and the interarrival time follow the same geometric distribution:
\begin{equation*} \lim_{t\to\infty} \frac{C_T}{t}\xrightarrow{t\to\infty} \frac{\mathbb{E}(R_i)}{\mathbb{E}(T)} = \frac{p}{p} = 1 \end{equation*}
And then the result would just be $\frac{1}{m}$. Would that be right?