Cumulants vs. moments












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In high order statistics, what is the intuition for the difference between cumulants and moments? What does any of them measure and what is the intuition to use one of them over the other?



Specifically, I am following this paper, and I am trying to understand their reasoning behind using cumulants. Why did they move from $G_n$ to $C_n$ after equation [6]? What are those cross-terms that exist in the correlation case and are not present in the cumulant case?










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    1














    In high order statistics, what is the intuition for the difference between cumulants and moments? What does any of them measure and what is the intuition to use one of them over the other?



    Specifically, I am following this paper, and I am trying to understand their reasoning behind using cumulants. Why did they move from $G_n$ to $C_n$ after equation [6]? What are those cross-terms that exist in the correlation case and are not present in the cumulant case?










    share|cite|improve this question



























      1












      1








      1


      1





      In high order statistics, what is the intuition for the difference between cumulants and moments? What does any of them measure and what is the intuition to use one of them over the other?



      Specifically, I am following this paper, and I am trying to understand their reasoning behind using cumulants. Why did they move from $G_n$ to $C_n$ after equation [6]? What are those cross-terms that exist in the correlation case and are not present in the cumulant case?










      share|cite|improve this question















      In high order statistics, what is the intuition for the difference between cumulants and moments? What does any of them measure and what is the intuition to use one of them over the other?



      Specifically, I am following this paper, and I am trying to understand their reasoning behind using cumulants. Why did they move from $G_n$ to $C_n$ after equation [6]? What are those cross-terms that exist in the correlation case and are not present in the cumulant case?







      moment-generating-functions cumulants






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      edited 2 days ago

























      asked Dec 27 '18 at 7:43









      havakok

      510215




      510215






















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          The cumulant is the part of the moment that is not "caused" by lower order moments.



          To get intuition, consider the case where the measurements are all the same, $X_i=x$, Then the $n$th moment is $langle X^nrangle=x^n=langle Xrangle^n$ , whereas the cumulants would all be $0$ starting from $n=2$. If we have non identical measurements each moment can be written as a sum of products lower moments and a "new" term. This new term is the cumulant.



          As an example, consider the 3rd moment $<X^3>$. We write it as $$<((X-<X>)+<X>)^3>=<(X-<X>)^3+3(X-<X>)^2<X>+3(X-<X>)<X>^2+<X>^3>$$, recalling that $<X-<X>>=0$, we can write
          $$<X^3>=<(X-<X>)^3>+3<(X-<X>)^2><X>+<X>^3$$. the term $(X-<X>)^3$ cannot be written in terms of $<X>;<(X-<X>)^2>$ and is the 3 order cumulant.






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          • 1




            @hardmath I added the 3rd moment case.
            – user617446
            2 days ago











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          1 Answer
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          active

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          active

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          2





          +50









          The cumulant is the part of the moment that is not "caused" by lower order moments.



          To get intuition, consider the case where the measurements are all the same, $X_i=x$, Then the $n$th moment is $langle X^nrangle=x^n=langle Xrangle^n$ , whereas the cumulants would all be $0$ starting from $n=2$. If we have non identical measurements each moment can be written as a sum of products lower moments and a "new" term. This new term is the cumulant.



          As an example, consider the 3rd moment $<X^3>$. We write it as $$<((X-<X>)+<X>)^3>=<(X-<X>)^3+3(X-<X>)^2<X>+3(X-<X>)<X>^2+<X>^3>$$, recalling that $<X-<X>>=0$, we can write
          $$<X^3>=<(X-<X>)^3>+3<(X-<X>)^2><X>+<X>^3$$. the term $(X-<X>)^3$ cannot be written in terms of $<X>;<(X-<X>)^2>$ and is the 3 order cumulant.






          share|cite|improve this answer



















          • 1




            @hardmath I added the 3rd moment case.
            – user617446
            2 days ago
















          2





          +50









          The cumulant is the part of the moment that is not "caused" by lower order moments.



          To get intuition, consider the case where the measurements are all the same, $X_i=x$, Then the $n$th moment is $langle X^nrangle=x^n=langle Xrangle^n$ , whereas the cumulants would all be $0$ starting from $n=2$. If we have non identical measurements each moment can be written as a sum of products lower moments and a "new" term. This new term is the cumulant.



          As an example, consider the 3rd moment $<X^3>$. We write it as $$<((X-<X>)+<X>)^3>=<(X-<X>)^3+3(X-<X>)^2<X>+3(X-<X>)<X>^2+<X>^3>$$, recalling that $<X-<X>>=0$, we can write
          $$<X^3>=<(X-<X>)^3>+3<(X-<X>)^2><X>+<X>^3$$. the term $(X-<X>)^3$ cannot be written in terms of $<X>;<(X-<X>)^2>$ and is the 3 order cumulant.






          share|cite|improve this answer



















          • 1




            @hardmath I added the 3rd moment case.
            – user617446
            2 days ago














          2





          +50







          2





          +50



          2




          +50




          The cumulant is the part of the moment that is not "caused" by lower order moments.



          To get intuition, consider the case where the measurements are all the same, $X_i=x$, Then the $n$th moment is $langle X^nrangle=x^n=langle Xrangle^n$ , whereas the cumulants would all be $0$ starting from $n=2$. If we have non identical measurements each moment can be written as a sum of products lower moments and a "new" term. This new term is the cumulant.



          As an example, consider the 3rd moment $<X^3>$. We write it as $$<((X-<X>)+<X>)^3>=<(X-<X>)^3+3(X-<X>)^2<X>+3(X-<X>)<X>^2+<X>^3>$$, recalling that $<X-<X>>=0$, we can write
          $$<X^3>=<(X-<X>)^3>+3<(X-<X>)^2><X>+<X>^3$$. the term $(X-<X>)^3$ cannot be written in terms of $<X>;<(X-<X>)^2>$ and is the 3 order cumulant.






          share|cite|improve this answer














          The cumulant is the part of the moment that is not "caused" by lower order moments.



          To get intuition, consider the case where the measurements are all the same, $X_i=x$, Then the $n$th moment is $langle X^nrangle=x^n=langle Xrangle^n$ , whereas the cumulants would all be $0$ starting from $n=2$. If we have non identical measurements each moment can be written as a sum of products lower moments and a "new" term. This new term is the cumulant.



          As an example, consider the 3rd moment $<X^3>$. We write it as $$<((X-<X>)+<X>)^3>=<(X-<X>)^3+3(X-<X>)^2<X>+3(X-<X>)<X>^2+<X>^3>$$, recalling that $<X-<X>>=0$, we can write
          $$<X^3>=<(X-<X>)^3>+3<(X-<X>)^2><X>+<X>^3$$. the term $(X-<X>)^3$ cannot be written in terms of $<X>;<(X-<X>)^2>$ and is the 3 order cumulant.







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited 2 days ago

























          answered 2 days ago









          user617446

          4443




          4443








          • 1




            @hardmath I added the 3rd moment case.
            – user617446
            2 days ago














          • 1




            @hardmath I added the 3rd moment case.
            – user617446
            2 days ago








          1




          1




          @hardmath I added the 3rd moment case.
          – user617446
          2 days ago




          @hardmath I added the 3rd moment case.
          – user617446
          2 days ago


















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