Chapter 5: Problem 6
Show that the renewal function corresponding to the lifetime density $$ f(x)=\lambda^{2} x e^{-2 x}, \quad x \geq 0 $$ is $$ M(t)=\frac{1}{2} \lambda t-\frac{1}{4}\left(1-e^{-2 \lambda t}\right) $$
Chapter 5: Problem 6
Show that the renewal function corresponding to the lifetime density $$ f(x)=\lambda^{2} x e^{-2 x}, \quad x \geq 0 $$ is $$ M(t)=\frac{1}{2} \lambda t-\frac{1}{4}\left(1-e^{-2 \lambda t}\right) $$
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Get started for freeLet \(X_{1}, X_{2}, \ldots\), be the interoccurrence times in a renewal process. Suppose \(\operatorname{Pr}\left\\{X_{k}=1\right\\}=p\) and \(\operatorname{Pr}\left\\{X_{k}=2\right\\}=q=1-p .\) Verify that $$ E\left[N_{n}\right]=\frac{n}{1+q}-\frac{q^{2}}{(1+q)^{2}}+\frac{q^{n+2}}{(1+q)^{2}}, \quad n=2,4, \ldots $$ where \(N_{n}\) is the mean number of renewals up to (discrete time) \(n\).
Determine the distribution of the total life \(\beta_{t}\) of the Poisson process.
Consider a renewal process with underlying distribution function \(F(x)\). Let \(\mathbb{W}\) be the time when the interval duration from the preceding renewal event first exceeds \(\xi>0\) (a fixed constant). Determine an integral equation satisfied by $$ V(t)=\operatorname{Pr}\\{W \leq t\\} $$ Calculate \(E[W] .\) (Assume an event occurs at time \(t=0 .\) )
For a renewal process with distribution \(F(x)\) compute $$ p(t)=\operatorname{Pr}\\{\text { number of renewals in }(0, t] \text { is odd }\\} $$ Obtain this explicitly for a Poisson process with parameter \(\lambda\) and also explicitly when \(F(t)=\int_{0}^{1} x e^{-x} d x\).
Consider a renewal process \(N(t)\) with associated distribution function \(F(x)\). Define \(m_{k}(t)=E\left[N(t)^{h}\right]\). Show that \(m_{k}(t)\) satisfies the renewal equation $$ m_{k}(t)=z_{k}(t)+\int_{0}^{t} m_{k}(t-\tau) d F(\tau), \quad k=1,2, \ldots $$ where $$ z_{k}(t)=\int_{0}^{t} \sum_{j=0}^{k-1}\left(\begin{array}{l} k \\ j \end{array}\right) m_{j}(t-\tau) d F(\tau) $$ Ilint: Use the renewal argument.
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