Resolving this summation using the given pmf











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So I'm trying to derive an expected value (related to Bayesian risk/loss function) and I've derived all except one final part. To finish the final part I need to derive one of the following expected values (either will work)



Define the probability mass function



$$p_N (n) = {n-1 choose x-1} frac{Gamma(a+b)}{Gamma(a) + Gamma(b)}frac{Gamma(a+x)+Gamma(b+n-x)}{Gamma(a+b+n)}$$



for $n =x,x+1,x+2,dots$ and also define the conditional pmf



$$p_N(n|p) = {n-1 choose x-1} p^x (1-p)^{n-x}$$



To complete the final step I need either one of:



$$E_N left[ left(frac{x-1}{N-1} right)^2right]$$



or



$$E_{N} = left[ left(frac{x-1}{N-1} right)^2 bigg| p right]$$



In previous questions, I've derived the necessary expected values by absorbing the terms into the probability functions in order to construct a new distribution function, and then obtaining the expected value by normalizing it so that it sums/integrates to $1$. But for these ones I'm stuck due to the fact it's squared and you're left with a single fraciton that can't be absorbed into the combination.



Does anyone see a way forward?










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    up vote
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    So I'm trying to derive an expected value (related to Bayesian risk/loss function) and I've derived all except one final part. To finish the final part I need to derive one of the following expected values (either will work)



    Define the probability mass function



    $$p_N (n) = {n-1 choose x-1} frac{Gamma(a+b)}{Gamma(a) + Gamma(b)}frac{Gamma(a+x)+Gamma(b+n-x)}{Gamma(a+b+n)}$$



    for $n =x,x+1,x+2,dots$ and also define the conditional pmf



    $$p_N(n|p) = {n-1 choose x-1} p^x (1-p)^{n-x}$$



    To complete the final step I need either one of:



    $$E_N left[ left(frac{x-1}{N-1} right)^2right]$$



    or



    $$E_{N} = left[ left(frac{x-1}{N-1} right)^2 bigg| p right]$$



    In previous questions, I've derived the necessary expected values by absorbing the terms into the probability functions in order to construct a new distribution function, and then obtaining the expected value by normalizing it so that it sums/integrates to $1$. But for these ones I'm stuck due to the fact it's squared and you're left with a single fraciton that can't be absorbed into the combination.



    Does anyone see a way forward?










    share|cite|improve this question
























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      So I'm trying to derive an expected value (related to Bayesian risk/loss function) and I've derived all except one final part. To finish the final part I need to derive one of the following expected values (either will work)



      Define the probability mass function



      $$p_N (n) = {n-1 choose x-1} frac{Gamma(a+b)}{Gamma(a) + Gamma(b)}frac{Gamma(a+x)+Gamma(b+n-x)}{Gamma(a+b+n)}$$



      for $n =x,x+1,x+2,dots$ and also define the conditional pmf



      $$p_N(n|p) = {n-1 choose x-1} p^x (1-p)^{n-x}$$



      To complete the final step I need either one of:



      $$E_N left[ left(frac{x-1}{N-1} right)^2right]$$



      or



      $$E_{N} = left[ left(frac{x-1}{N-1} right)^2 bigg| p right]$$



      In previous questions, I've derived the necessary expected values by absorbing the terms into the probability functions in order to construct a new distribution function, and then obtaining the expected value by normalizing it so that it sums/integrates to $1$. But for these ones I'm stuck due to the fact it's squared and you're left with a single fraciton that can't be absorbed into the combination.



      Does anyone see a way forward?










      share|cite|improve this question













      So I'm trying to derive an expected value (related to Bayesian risk/loss function) and I've derived all except one final part. To finish the final part I need to derive one of the following expected values (either will work)



      Define the probability mass function



      $$p_N (n) = {n-1 choose x-1} frac{Gamma(a+b)}{Gamma(a) + Gamma(b)}frac{Gamma(a+x)+Gamma(b+n-x)}{Gamma(a+b+n)}$$



      for $n =x,x+1,x+2,dots$ and also define the conditional pmf



      $$p_N(n|p) = {n-1 choose x-1} p^x (1-p)^{n-x}$$



      To complete the final step I need either one of:



      $$E_N left[ left(frac{x-1}{N-1} right)^2right]$$



      or



      $$E_{N} = left[ left(frac{x-1}{N-1} right)^2 bigg| p right]$$



      In previous questions, I've derived the necessary expected values by absorbing the terms into the probability functions in order to construct a new distribution function, and then obtaining the expected value by normalizing it so that it sums/integrates to $1$. But for these ones I'm stuck due to the fact it's squared and you're left with a single fraciton that can't be absorbed into the combination.



      Does anyone see a way forward?







      combinatorics summation expected-value






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      asked Nov 14 at 7:40









      Xiaomi

      911114




      911114






















          1 Answer
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          Hint using generating functions :



          begin{align*}
          sum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^n&=qsum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^{n-1}\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{(n-1)} q^{n-2} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} frac{1}{(n-1)} q^{n-1} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} int q^{n-2} dq dq\
          &=qint frac{1}{q} int left[sum_{n=x}^infty {n-1choose x-1} q^{n-2}right] dq dq\
          &=qint frac{1}{q} int (1-q)^{-x} q^{x-2} dq dq\
          end{align*}





          The combinatorics identity I use can be proved using the following argument :
          begin{align*}
          S(x,q)&=sum_{n=x}^infty {n-1choose x-1} q^n\
          &= sum_{n=x}^infty left [ {nchoose x} - {n-1 choose x}right] q^n\
          &=sum_{n=x}^infty {nchoose x}q^n - sum_{n=x}^infty{n-1 choose x} q^n\
          &= frac{1}{q}sum_{n=x+1}^infty {n-1choose x}q^n - sum_{n=x+1}^infty {n-1 choose x} q^n\
          &= left( frac{1}{q} - 1 right) S(x+1, q)
          end{align*}



          Which means that $S(x,q) = left( frac{q}{1-q} right)^{x-1} S(1,q)=left( frac{q}{1-q} right)^{x-1} sum_{n=1}^infty {n-1choose 0} q^n=left( frac{q}{1-q} right)^x$






          share|cite|improve this answer























          • Thanks Quinton, I've never encountered this method before :)
            – Xiaomi
            Nov 15 at 0:51











          Your Answer





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          up vote
          1
          down vote



          accepted










          Hint using generating functions :



          begin{align*}
          sum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^n&=qsum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^{n-1}\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{(n-1)} q^{n-2} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} frac{1}{(n-1)} q^{n-1} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} int q^{n-2} dq dq\
          &=qint frac{1}{q} int left[sum_{n=x}^infty {n-1choose x-1} q^{n-2}right] dq dq\
          &=qint frac{1}{q} int (1-q)^{-x} q^{x-2} dq dq\
          end{align*}





          The combinatorics identity I use can be proved using the following argument :
          begin{align*}
          S(x,q)&=sum_{n=x}^infty {n-1choose x-1} q^n\
          &= sum_{n=x}^infty left [ {nchoose x} - {n-1 choose x}right] q^n\
          &=sum_{n=x}^infty {nchoose x}q^n - sum_{n=x}^infty{n-1 choose x} q^n\
          &= frac{1}{q}sum_{n=x+1}^infty {n-1choose x}q^n - sum_{n=x+1}^infty {n-1 choose x} q^n\
          &= left( frac{1}{q} - 1 right) S(x+1, q)
          end{align*}



          Which means that $S(x,q) = left( frac{q}{1-q} right)^{x-1} S(1,q)=left( frac{q}{1-q} right)^{x-1} sum_{n=1}^infty {n-1choose 0} q^n=left( frac{q}{1-q} right)^x$






          share|cite|improve this answer























          • Thanks Quinton, I've never encountered this method before :)
            – Xiaomi
            Nov 15 at 0:51















          up vote
          1
          down vote



          accepted










          Hint using generating functions :



          begin{align*}
          sum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^n&=qsum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^{n-1}\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{(n-1)} q^{n-2} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} frac{1}{(n-1)} q^{n-1} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} int q^{n-2} dq dq\
          &=qint frac{1}{q} int left[sum_{n=x}^infty {n-1choose x-1} q^{n-2}right] dq dq\
          &=qint frac{1}{q} int (1-q)^{-x} q^{x-2} dq dq\
          end{align*}





          The combinatorics identity I use can be proved using the following argument :
          begin{align*}
          S(x,q)&=sum_{n=x}^infty {n-1choose x-1} q^n\
          &= sum_{n=x}^infty left [ {nchoose x} - {n-1 choose x}right] q^n\
          &=sum_{n=x}^infty {nchoose x}q^n - sum_{n=x}^infty{n-1 choose x} q^n\
          &= frac{1}{q}sum_{n=x+1}^infty {n-1choose x}q^n - sum_{n=x+1}^infty {n-1 choose x} q^n\
          &= left( frac{1}{q} - 1 right) S(x+1, q)
          end{align*}



          Which means that $S(x,q) = left( frac{q}{1-q} right)^{x-1} S(1,q)=left( frac{q}{1-q} right)^{x-1} sum_{n=1}^infty {n-1choose 0} q^n=left( frac{q}{1-q} right)^x$






          share|cite|improve this answer























          • Thanks Quinton, I've never encountered this method before :)
            – Xiaomi
            Nov 15 at 0:51













          up vote
          1
          down vote



          accepted







          up vote
          1
          down vote



          accepted






          Hint using generating functions :



          begin{align*}
          sum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^n&=qsum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^{n-1}\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{(n-1)} q^{n-2} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} frac{1}{(n-1)} q^{n-1} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} int q^{n-2} dq dq\
          &=qint frac{1}{q} int left[sum_{n=x}^infty {n-1choose x-1} q^{n-2}right] dq dq\
          &=qint frac{1}{q} int (1-q)^{-x} q^{x-2} dq dq\
          end{align*}





          The combinatorics identity I use can be proved using the following argument :
          begin{align*}
          S(x,q)&=sum_{n=x}^infty {n-1choose x-1} q^n\
          &= sum_{n=x}^infty left [ {nchoose x} - {n-1 choose x}right] q^n\
          &=sum_{n=x}^infty {nchoose x}q^n - sum_{n=x}^infty{n-1 choose x} q^n\
          &= frac{1}{q}sum_{n=x+1}^infty {n-1choose x}q^n - sum_{n=x+1}^infty {n-1 choose x} q^n\
          &= left( frac{1}{q} - 1 right) S(x+1, q)
          end{align*}



          Which means that $S(x,q) = left( frac{q}{1-q} right)^{x-1} S(1,q)=left( frac{q}{1-q} right)^{x-1} sum_{n=1}^infty {n-1choose 0} q^n=left( frac{q}{1-q} right)^x$






          share|cite|improve this answer














          Hint using generating functions :



          begin{align*}
          sum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^n&=qsum_{n=x}^infty {n-1choose x-1} frac{1}{(n-1)^2} q^{n-1}\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{(n-1)} q^{n-2} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} frac{1}{(n-1)} q^{n-1} dq\
          &=qsum_{n=x}^infty {n-1choose x-1} int frac{1}{q} int q^{n-2} dq dq\
          &=qint frac{1}{q} int left[sum_{n=x}^infty {n-1choose x-1} q^{n-2}right] dq dq\
          &=qint frac{1}{q} int (1-q)^{-x} q^{x-2} dq dq\
          end{align*}





          The combinatorics identity I use can be proved using the following argument :
          begin{align*}
          S(x,q)&=sum_{n=x}^infty {n-1choose x-1} q^n\
          &= sum_{n=x}^infty left [ {nchoose x} - {n-1 choose x}right] q^n\
          &=sum_{n=x}^infty {nchoose x}q^n - sum_{n=x}^infty{n-1 choose x} q^n\
          &= frac{1}{q}sum_{n=x+1}^infty {n-1choose x}q^n - sum_{n=x+1}^infty {n-1 choose x} q^n\
          &= left( frac{1}{q} - 1 right) S(x+1, q)
          end{align*}



          Which means that $S(x,q) = left( frac{q}{1-q} right)^{x-1} S(1,q)=left( frac{q}{1-q} right)^{x-1} sum_{n=1}^infty {n-1choose 0} q^n=left( frac{q}{1-q} right)^x$







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited Nov 14 at 8:42

























          answered Nov 14 at 8:02









          P. Quinton

          1,261213




          1,261213












          • Thanks Quinton, I've never encountered this method before :)
            – Xiaomi
            Nov 15 at 0:51


















          • Thanks Quinton, I've never encountered this method before :)
            – Xiaomi
            Nov 15 at 0:51
















          Thanks Quinton, I've never encountered this method before :)
          – Xiaomi
          Nov 15 at 0:51




          Thanks Quinton, I've never encountered this method before :)
          – Xiaomi
          Nov 15 at 0:51


















           

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