Let $\left(X_{t}, t \geq 0\right)$ be a renewal process with holding times $\left(S_{n}, n=1,2, \ldots\right)$ and $\left(Y_{t}, t \geq 0\right)$ be a renewal-reward process over $\left(X_{t}\right)$ with a sequence of rewards $\left(W_{n}, n=1,2, \ldots\right)$. Under assumptions on $\left(S_{n}\right)$ and $\left(W_{n}\right)$ which you should state clearly, prove that the ratios

$$X_{t} / t \text { and } Y_{t} / t$$

converge as $t \rightarrow \infty$. You should specify the form of convergence guaranteed by your assumptions. The law of large numbers, in the appropriate form, for sums $S_{1}+\ldots+S_{n}$ and $W_{1}+\ldots+W_{n}$ can be used without proof.

In a mountain resort, when you rent skiing equipment you are given two options. (1) You buy an insurance waiver that costs $C / 4$ where $C$ is the daily equipment rent. Under this option, the shop will immediately replace, at no cost to you, any piece of equipment you break during the day, no matter how many breaks you had. (2) If you don't buy the waiver, you'll pay $3 C$ in the case of any break.

To find out which option is better for me, I decided to set up two models of renewalreward process $\left(Y_{t}\right)$. In the first model, (Option 1), all of the holding times $S_{n}$ are equal to 6 . In the second model, given that there is no break on day $n$ (an event of probability $4 / 5)$, we have $S_{n}=6, W_{n}=C$, but given that there is a break on day $n$, we have that $S_{n}$ is uniformly distributed on $(0,6)$, and $W_{n}=4 C$. (In the second model, I would not continue skiing after a break, whereas in the first I would.)

Calculate in each of these models the limit

$$\lim _{t \rightarrow \infty} Y_{t} / t$$

representing the long-term average cost of a unit of my skiing time.