Sunday, 27 April 2008

st.statistics - Distribution of the sum of the m smallest values in a sample of size n

This is following on from Douglas Zare's answer. While not an answer in its own right,it was getting too long for a comment. Briefly, we can hit the question with brute force and look for a generating function for the desired expected values.



So, put
fj(y)=sumj1k=0nchoosekyk(1y)nk


so that using the notation of Douglas' answer, gj(x)=fj(F(x)), and the expectation of the jth order statistic is
Ej:=inti0nftyfj(F(x))dx



Put G(y,z)=sumnj=1fj(y)zj where z is a formal variable. By linearity we have
sumnj=1Ejzj=inti0nftyG(F(x),z)dx



We can try to write G as a rational function in y and z.
Expanding out and interchanging the order of summation gives
eqalign{ G(y,z) & = sum_{j=1}^nsum_{k=0}^{j-1} {nchoose k} y^k (1-y)^{n-k} z^j \\        & = sum_{k=0}^{n-1} sum_{j=k+1}^n z^j {nchoose k} y^k (1-y)^{n-k} \\        & = sum_{k=0}^{n-1} left( sum_{j=1}^{n-k} z^j right) cdot z^k{nchoose k} y^k (1-y)^{n-k} \\ }



Now
eqalign{ sum_{j=1}^{M-1}jz^j   = z frac{d}{dz}sum_{j=0}^{M-1} z^j  & = z frac{d}{dz}left[frac{1-z^M}{1-z}right] \\  & = frac{z-z^{M+1}}{(1-z)^2} - frac{Mz^M}{1-z}   & = frac{z-z^M}{(1-z)^2} - frac{(M-1)z^M}{1-z} }


so substituting this back in we get
eqalign{ G(y,z)  & = sum_{k=0}^{n-1} left[ frac{z-z^{n-k+1}}{(1-z)^2} - frac{(n-k)z^{n-k+1}}{1-z} right] cdot z^k{nchoose k} y^k (1-y)^{n-k} \\  & = sum_{k=0}^{n-1} frac{z}{(1-z)^2}{nchoose k} (yz)^k (1-y)^{n-k}  \\  &   - sum_{k=0}^{n-1} frac{z^{n+1}}{(1-z)^2}  {nchoose k} y^k (1-y)^{n-k}  \\  &   - sum_{k=0}^{n-1} frac{nz^{n+1}}{1-z} { {n-1} choose k } y^k(1-y)^{n-k} \\  & = frac{z}{(1-z)^2} left[ (1-y+yz)^n - (yz)^n right]  - frac{z^{n+1}}{(1-z)^2} (1-y^n)   - frac{nz^{n+1}}{1-z} }



I guess that in theory one could plug this back in to obtain a "formula" for the generating function sumnj=1Ejzj, but I can't see how that formula might then simplify to something calculable, unless F has a rather special form.

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