Question #48727

If X and Y are i.i.d r.v.s with 〖fx (x)=α∙e〗^(-αx) u(x) and 〖fY (y)=α∙e〗^(-αy) u(y). Find the pdf fz (z) for Z=2X+Y.
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Expert's answer

2014-11-13T09:04:28-0500

Answer on Question #48727 – Math – Statistics and Probability

If XX and YY are i.i.d r.v.s with fX(x)=αeαxf_{X}(x) = \alpha \cdot e^{-\alpha x}, u(x)u(x) and fY(y)=αeαyu(y)f_{Y}(y) = \alpha \cdot e^{-\alpha y}u(y). Find the pdf fZ(z)f_{Z}(z) for


Z=2X+Y.Z = 2X + Y.

Solution

F2X(t)=P(2X<t)=P(X<t2)=FX(t2),F_{2X}(t) = P(2X < t) = P\left(X < \frac{t}{2}\right) = F_{X}\left(\frac{t}{2}\right),


Find probability distribution function of 2X2X:


f2X(t)=ddtF2X(t)=ddtFX(t2)=12fX(t2)=α2eαt2u(t2), where u(t)=1 when t0;f_{2X}(t) = \frac{d}{dt} F_{2X}(t) = \frac{d}{dt} F_{X}\left(\frac{t}{2}\right) = \frac{1}{2} f_{X}\left(\frac{t}{2}\right) = \frac{\alpha}{2} \cdot e^{-\frac{\alpha t}{2}} u\left(\frac{t}{2}\right), \text{ where } u(t) = 1 \text{ when } t \geq 0;u(t)=0 when t<0.u(t) = 0 \text{ when } t < 0.


The probability density function of the sum of two independent random variables 2X2X and YY, each of which has a probability density function, is the convolution of their separate density functions:


fZ(z)=f2X+Y(z)=+f2X(x)fY(zx)dx=+α2eαx2u(x2)αeα(zx)u(zx))dx=αα220zeαz+αx2dx=αeαzeαx20zu(z)=αeαz(eαz21)u(z)=αeαz2(1eαz2)u(z).f_{Z}(z) = f_{2X + Y}(z) = \int_{-\infty}^{+\infty} f_{2X}(x) f_{Y}(z - x) dx = \int_{-\infty}^{+\infty} \frac{\alpha}{2} \cdot e^{-\frac{\alpha x}{2}} u\left(\frac{x}{2}\right) \alpha \cdot e^{-\alpha(z - x)} u(z - x)) dx = \alpha \frac{\alpha^{2}}{2} \int_{0}^{z} e^{-\alpha z + \frac{\alpha x}{2}} dx = \alpha e^{-\alpha z} \left. e^{\frac{\alpha x}{2}} \right|_{0}^{z} u(z) = \alpha e^{-\alpha z} \left(e^{\frac{\alpha z}{2}} - 1\right) u(z) = \alpha e^{-\frac{\alpha z}{2}} \left(1 - e^{-\frac{\alpha z}{2}}\right) u(z).


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