The mean of order statistics

GSaud

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I am trying to compute the mean of the i-th order statistics for \(\displaystyle n\) Rayleigh random variables as follows:

. . . . .\(\displaystyle \large{ \displaystyle \int_0^{\infty}\, A \, x \, F^{i-1} (1\,-\,F)^{n-i} \, f \, dx }\)

where

. . . . .\(\displaystyle \large{ A\, =\, i\, \binom{n}{i} \, \mbox{ and }\, F\,=\,1\,-\,e^{\frac{-x^2}{2\sigma^2}} }\)

is the CDF of the Rayleigh RV and

. . . . .\(\displaystyle \large{ f\,=\,\frac{x}{\sigma^2}e^{\frac{-x^2}{2\sigma^2}} }\)

is its pdf.

I start by substituting \(\displaystyle p\,=\,1\,-\,F\), changing the integral limits to between \(\displaystyle 0\) and \(\displaystyle 1\) and then substituting the values of

. . . . .\(\displaystyle \large{ \displaystyle x\, =\, \left(-2\,\sigma^2\, \ln(P)\right)^{\frac{1}{2}}\, =\, \sigma\,\sqrt{\strut 2\,}\left(\ln\left(\frac{1}{p}\right)\right)^{1/2} }\)

The integral becomes:

. . . . .\(\displaystyle \large{ \displaystyle A\, \sqrt{\strut 2\,}\, \sigma\,\int_0^1 \, \left(\ln\left(\frac{1}{p}\right)\right)^{1/2} \,(1\,-\,p)^{i-1}\, P^{n-i}\, dp }\)

Then, by using integration by parts:

. . . . .\(\displaystyle \large{ \displaystyle -A \,\sqrt{\strut 2\,} \, \sigma \, \Gamma\left(\frac{3}{2}\right)\, \bigg[ (n\,-\,i) \,\beta (n-i,\,i) \,-\, (i\,-\,1) \,\beta(n\,-\,i\,+\,1,\, i\,=\,1)\bigg] }\)

where \(\displaystyle \Gamma\) is the Gamma function and \(\displaystyle \beta\) is the Beta function.

In the integration by parts, I use

. . . . .\(\displaystyle \large{ \displaystyle u\,=\, (1\,-\,p)^{i-1}\,P^{n-i} \, \mbox{ and }\, dv\,=\, \left(\ln\left(\frac{1}{p}\right)\right)^{1/2} \, dp }\)

The problem is that I have run a simulation for these values and the results are different from the theoretical results I derived. Could you please help me in finding any mistakes I may have made?
 
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I am trying to compute the mean of the i-th order statistics for \(\displaystyle n\) Rayleigh random variables as follows:

2. . . . .\(\displaystyle \large{ \displaystyle \int_0^{\infty}\, A \, x \, F^{i-1} (1\,-\,F)^{n-i} \, f \, dx }\)

where

. . . . .\(\displaystyle \large{ A\, =\, i\, \binom{n}{i} \, \mbox{ and }\, F\,=\,1\,-\,e^{\frac{-x^2}{2\sigma^2}} }\)

is the CDF of the Rayleigh RV and

. . . . .\(\displaystyle \large{ f\,=\,\frac{x}{\sigma^2}e^{\frac{-x^2}{2\sigma^2}} }\)

is its pdf.

I start by substituting \(\displaystyle p\,=\,1\,-\,F\), changing the integral limits to between \(\displaystyle 0\) and \(\displaystyle 1\) and then substituting the values of

. . . . .\(\displaystyle \large{ \displaystyle x\, =\, \left(-2\,\sigma^2\, \ln(P)\right)^{\frac{1}{2}}\, =\, \sigma\,\sqrt{\strut 2\,}\left(\ln\left(\frac{1}{p}\right)\right)^{1/2} }\)

The integral becomes:

. . . . .\(\displaystyle \large{ \displaystyle A\, \sqrt{\strut 2\,}\, \sigma\,\int_0^1 \, \left(\ln\left(\frac{1}{p}\right)\right)^{1/2} \,(1\,-\,p)^{i-1}\, P^{n-i}\, dp }\)

Then, by using integration by parts:

. . . . .\(\displaystyle \large{ \displaystyle -A \,\sqrt{\strut 2\,} \, \sigma \, \Gamma\left(\frac{3}{2}\right)\, \bigg[ (n\,-\,i) \,\beta (n-i,\,i) \,-\, (i\,-\,1) \,\beta(n\,-\,i\,+\,1,\, i\,=\,1)\bigg] }\)

where \(\displaystyle \Gamma\) is the Gamma function and \(\displaystyle \beta\) is the Beta function.

In the integration by parts, I use

. . . . .\(\displaystyle \large{ \displaystyle u\,=\, (1\,-\,p)^{i-1}\,P^{n-i} \, \mbox{ and }\, dv\,=\, \left(\ln\left(\frac{1}{p}\right)\right)^{1/2} \, dp }\)

The problem is that I have run a simulation for these values and the results are different from the theoretical results I derived. Could you please help me in finding any mistakes I may have made?
Since

. . . . .\(\displaystyle x\, =\, \sqrt{\strut 2\,}\, \sigma\, \sqrt{\strut \ln(p^{-1})\,}\)

I get

. . . . .\(\displaystyle dx\, =\, -\dfrac{\sqrt{\strut 2\,}\, \sigma\, dp}{p\, \sqrt{\strut \ln(p^{-1})\,}}\, =\, -\dfrac{2\, \sigma^2\, dp}{p\, \left[\sqrt{\strut 2\,}\, \sigma\, \sqrt{\ln(p^{-1})} \right]}\, =\, -\dfrac{2\, \sigma^2\, dp}{p\, x}\)

and a different final integral.

Although there may be a different way to go about it, I would probably re-write the original series as a finite sum of expected values of Gaussians with different standard deviations if n and i were not large. That is, since the integral form doesn't change if we use

. . . . .\(\displaystyle \large{ F \,=\, e^{\frac{-x^2}{2\, \sigma^2}} }\)

and since f = - F', we can write the original equation as

. . . . .\(\displaystyle -\large{ \displaystyle \int_0^{\infty}\, A \, x \, F^{n-i} (1\,-\,F)^{i-1} \, F' \, dx }\)

. . . . . . . . . .\(\displaystyle =\, \large{ \displaystyle \int_0^{\infty}\, \underset{k}{\Sigma}\,\alpha_k\, x \, F^{k}\, F^{'} \, dx }\)
 
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