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Consider a random variable $Y$ with complex Gaussian distribution, i.e $Y \sim \mathcal{C N}(\mu,\sigma^2)$. We can write $Y$ as real ($Y_r$) and imaginary component ($Y_j$) as $Y = Y_r + i Y_j$. Where, $Y_r \sim \mathcal{N}(\mu,\sigma^2/2)$ and $Y_j \sim \mathcal{N}(0,\sigma^2/2)$.

Now, I am selecting $M$ samples from the $Y$ distribution such that their absolute value ($|Y|$) is bigger than other remaining $N-M$ samples, where $N$ is the total number of samples.

What is the mean and variance of these selected $M$ samples? Any bound or asymptotic approach will also work.

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    $\begingroup$ Whatever be the distribution of the r.v. of interest, here $Z:= |Y|$, your interest in on the $M$ largest order statistic. The distribution of the order statistic can be expressed in a closed form expression involving the distibution of $Z$. Maybe numerical ingegration can be used then. $\endgroup$
    – Yves
    Commented Apr 26, 2021 at 5:59
  • $\begingroup$ @Yves Can you please give me some fine references where I can study? I am new to this field and trying to get my head around. $\endgroup$
    – Ahwaq
    Commented May 11, 2021 at 6:04
  • $\begingroup$ There are many books with a chapter or section on order statistics; for instance the old good Mood Graybill & Boes Introduction to the Theory of Statistics. The marginal distributions of the order statistics are available on Wikipedia. $\endgroup$
    – Yves
    Commented May 11, 2021 at 14:59

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