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11-5 (20) Assume X1.X2Xn are IID random variables, each with density fx (x)-6x-(0+1)n(x-1) , where θ > 0 and u(x) İs the unit step function. Use the CLT to find the approximate pdf of the random variable Z- In((X,X2X]. What happens as n Hint: make a change of variable x -ey and integration by parts, or results at the end of this problem set.

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Answer #1

Given 1, 2, , Xn are IID random variables with PDF,

f_X\left ( x \right )=\theta x^{-\theta -1};x>1,\theta >0

Now the PDF of the random variable Y=g\left ( X \right )=\ln X is

f_Y\left ( y \right )=f_X\left ( g^{-1}\left ( y \right ) \right )\left | \frac{\mathrm{d} g^{-1}\left ( y \right ) }{\mathrm{d} y} \right |

Here X=e^Y\Rightarrow g^{-1}\left ( y \right )=e^y . Thus the PDF of Y=g\left ( X \right )=\ln X is

f_Y\left ( y \right )=\theta \left (e^y \right )^{-\theta -1}\left | \frac{\mathrm{d} e^y }{\mathrm{d} y} \right |\\ f_Y\left ( y \right )=\theta e^{-\theta y};y>0

Thst is the PDF of Y=g\left ( X \right )=\ln X is exponential.

Consider the random variable

Z=\ln\left ( X_1X_2... X_n \right )^{1/n}\\ Z=\frac{\ln X_1+\ln X_2+...+\ln X_n}{n}\\ Z=\frac{Y_1+Y_2+...+Y_n}{n}

According to CLT, the distribution of Z=\frac{Y_1+Y_2+...+Y_n}{n} is approximately normal with

\mu =E\left ( Y \right ),\sigma ^2=Var\left ( Y \right )/n

We know the mean of exponential random variable E\left ( Y \right )=1/\theta ,Var\left ( Y \right )=1/\theta ^2 .

Thus the approximate PDF of

{\color{Blue} Z=\ln\left ( X_1X_2... X_n \right )^{1/n}\sim N\left ( 1/\theta ,1/\left (n\theta ^2 \right )\right )}

When n\rightarrow \infty , the above PDF becomes,

Z=\ln\left ( X_1X_2... X_n \right )^{1/n}\sim \lim_{n\rightarrow \infty}N\left ( 1/\theta ,1/\left (n\theta ^2 \right )\right )

So the distribution is f_Z\left ( z \right )= \delta \left ( z-1/\theta \right );-\infty <z<\infty

The PDF becomes Dirac's delta function.

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