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S_David
Oct3-09, 05:23 AM
Hello,

Suppose that we have the following set of independent and identically distributed RVs: \gamma_1,\,\gamma_2,\,\ldots,\,\gamma_M. Arranging them in descending order as: \gamma_{1:M}\ge\gamma_{2:M}\ge\cdots\ge\gamma_{M:M }. Now suppose we select the largest m\leq M order statistics. What is the PDF of the selected set? Mathematically:

f_{\gamma_{1:M},\,\ldots,\,\gamma_{m:M}}(\gamma_{1 :M},\,\ldots,\,\gamma_{m:M})=??

Thanks in advance

EnumaElish
Oct4-09, 11:55 AM
What would f be for m = 1? How do you get there?

S_David
Oct4-09, 12:18 PM
What would f be for m = 1? How do you get there?

f_{\gamma_{1:M}}(\gamma)=\frac{d}{d\,\gamma}F_{\ga mma_{1:M}}(\gamma)=\frac{d}{d\,\gamma}\text{Pr}\le ft[\gamma_{1:M}\le\gamma\right]=\frac{d}{d\,\gamma}\text{Pr}\left[\gamma_{1}\le\gamma,\gamma_{2}\le\gamma,\ldots,\ga mma_{M}\le\gamma\right]=\frac{d}{d\,\gamma}\left[F_{\gamma}(\gamma)\right]^M

where F_{\gamma}(\gamma) is the CDF of the original set of RVs.

But when we pick a subset of the m^{\text{th}} largest order statistics, how can we treat the statistics? I mean I have the final answer from books and papers, but I didn't understand how they derive it.