How to construct an example for the entropy equation: $H(Z)=H(X)+H(Y)$ where $Z=X+Y$ [duplicate]

The name of the pictureThe name of the pictureThe name of the pictureClash Royale CLAN TAG#URR8PPP











up vote
2
down vote

favorite













This question already has an answer here:



  • Entropy of sum is sum of entropies

    3 answers



Given $Z=X+Y$ where X and Y are two random variables, under what conditions does $H(Z)=H(X)+H(Y)$?



Notice $Z$ is a function of $(X,Y)$, therefore $H(Z)leq H(X,Y)$, and $H(X,Y)leq H(X)+H(Y)-I(X;Y)$. Therefore when $Z$ and $(X,Y)$ is a one-to-one function and $X$ is independent of $Y$.



My question is, how to find an example that satisfy this problem ? I have a simple example that let $X=0$ so that $Z=Y$, which satisfy the conditions. However, can anyone gives a more non-trivial example ? Thanks.










share|cite|improve this question













marked as duplicate by leonbloy, user91500, Adrian Keister, Theoretical Economist, Brahadeesh Sep 12 at 17:31


This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.


















    up vote
    2
    down vote

    favorite













    This question already has an answer here:



    • Entropy of sum is sum of entropies

      3 answers



    Given $Z=X+Y$ where X and Y are two random variables, under what conditions does $H(Z)=H(X)+H(Y)$?



    Notice $Z$ is a function of $(X,Y)$, therefore $H(Z)leq H(X,Y)$, and $H(X,Y)leq H(X)+H(Y)-I(X;Y)$. Therefore when $Z$ and $(X,Y)$ is a one-to-one function and $X$ is independent of $Y$.



    My question is, how to find an example that satisfy this problem ? I have a simple example that let $X=0$ so that $Z=Y$, which satisfy the conditions. However, can anyone gives a more non-trivial example ? Thanks.










    share|cite|improve this question













    marked as duplicate by leonbloy, user91500, Adrian Keister, Theoretical Economist, Brahadeesh Sep 12 at 17:31


    This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
















      up vote
      2
      down vote

      favorite









      up vote
      2
      down vote

      favorite












      This question already has an answer here:



      • Entropy of sum is sum of entropies

        3 answers



      Given $Z=X+Y$ where X and Y are two random variables, under what conditions does $H(Z)=H(X)+H(Y)$?



      Notice $Z$ is a function of $(X,Y)$, therefore $H(Z)leq H(X,Y)$, and $H(X,Y)leq H(X)+H(Y)-I(X;Y)$. Therefore when $Z$ and $(X,Y)$ is a one-to-one function and $X$ is independent of $Y$.



      My question is, how to find an example that satisfy this problem ? I have a simple example that let $X=0$ so that $Z=Y$, which satisfy the conditions. However, can anyone gives a more non-trivial example ? Thanks.










      share|cite|improve this question














      This question already has an answer here:



      • Entropy of sum is sum of entropies

        3 answers



      Given $Z=X+Y$ where X and Y are two random variables, under what conditions does $H(Z)=H(X)+H(Y)$?



      Notice $Z$ is a function of $(X,Y)$, therefore $H(Z)leq H(X,Y)$, and $H(X,Y)leq H(X)+H(Y)-I(X;Y)$. Therefore when $Z$ and $(X,Y)$ is a one-to-one function and $X$ is independent of $Y$.



      My question is, how to find an example that satisfy this problem ? I have a simple example that let $X=0$ so that $Z=Y$, which satisfy the conditions. However, can anyone gives a more non-trivial example ? Thanks.





      This question already has an answer here:



      • Entropy of sum is sum of entropies

        3 answers







      information-theory entropy






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Sep 8 at 10:22









      SoManyProb_for_a_broken_heart.

      4881717




      4881717




      marked as duplicate by leonbloy, user91500, Adrian Keister, Theoretical Economist, Brahadeesh Sep 12 at 17:31


      This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.






      marked as duplicate by leonbloy, user91500, Adrian Keister, Theoretical Economist, Brahadeesh Sep 12 at 17:31


      This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.






















          2 Answers
          2






          active

          oldest

          votes

















          up vote
          2
          down vote













          To construct a proper example, as you found out yourself in a very nice fashion, there is a bijection between $Z$ and $(X,Y)$ (I suppose that random variables are discrete of course).



          Let $X'sim textBernoulli(frac 12)$ and $Ysim textBernoulli(frac 12)$. Set $X=2X'$ and take $Z=X+Y$. Then $Z$ is uniformly distributed over $0,1,2,3$ and $X$ and $Y$ are also uniformly distributed over $0,2$ and $0,1$. Therefore it is easy to see that $H(Z)=H(X)+H(Y)$.






          share|cite|improve this answer




















          • I like your example +1
            – Ahmad Bazzi
            Sep 8 at 20:55

















          up vote
          1
          down vote













          In addition to the nice example @Arash gives. Assume the discrete uniform distribution. If $$X sim mathcal U_[a,b](n)$$and$$Y sim mathcal U_[c,d](m)$$
          Let's define $$Z = X+Y$$
          We know that the entropies of $X$ and $Y$ are $$H(X) = log n$$ and $$H(Y) = log m$$ therefore $$H(X) + H(Y) = log(n) + log(m) = log(nm)$$
          This means that if $Z$ has $nm$ outcomes, then we can assert that $H(Z) = H(X) + H(Y)$. Many examples could be generated here to demonstrate the need of being bijective.



          One Example out of MANY



          Assume $X in lbrace 1,2,3rbrace$ and $Y in lbrace 0,10,20 rbrace$. It is easy to see that $$Z in lbrace 1,2,3,11,12,13,21,22,23 rbrace$$ with $$P(Z = z) = frac19$$
          Is $H(Z) = ln(3times 3) = log 9$ ? Of course, because we $X+Y$ here is bijective.



          Let's prove it: $$H(Z) = sumlimits_k=1^9 p_k log(frac1p_k) = sumlimits_k=1^9 frac19 log(9) =9frac19 log(9) = log(9)$$



          Counter example



          Now let's take the same distributions (with different outcomes) but show that $H(Z)$ will not reach $log(9)$ if there is no bijectivity. Let $X in lbrace 0,1,2 rbrace$ and $Y in lbrace 3,4,5 rbrace $. So $$Z in lbrace 3,4,5,6,7 rbrace$$
          Therefore, it is clear there is no bijectivity, because $(1,3)$ and $(0,4)$ both give $Z = 4$, hence we can not decode $X,Y$ from $Z$.
          Computing the entropy $$H(Z) = frac19 log 9 + frac29 log frac92 +frac39 log frac93 + frac29 log frac92 + frac19 log 9 < log(9)$$






          share|cite|improve this answer





























            2 Answers
            2






            active

            oldest

            votes








            2 Answers
            2






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes








            up vote
            2
            down vote













            To construct a proper example, as you found out yourself in a very nice fashion, there is a bijection between $Z$ and $(X,Y)$ (I suppose that random variables are discrete of course).



            Let $X'sim textBernoulli(frac 12)$ and $Ysim textBernoulli(frac 12)$. Set $X=2X'$ and take $Z=X+Y$. Then $Z$ is uniformly distributed over $0,1,2,3$ and $X$ and $Y$ are also uniformly distributed over $0,2$ and $0,1$. Therefore it is easy to see that $H(Z)=H(X)+H(Y)$.






            share|cite|improve this answer




















            • I like your example +1
              – Ahmad Bazzi
              Sep 8 at 20:55














            up vote
            2
            down vote













            To construct a proper example, as you found out yourself in a very nice fashion, there is a bijection between $Z$ and $(X,Y)$ (I suppose that random variables are discrete of course).



            Let $X'sim textBernoulli(frac 12)$ and $Ysim textBernoulli(frac 12)$. Set $X=2X'$ and take $Z=X+Y$. Then $Z$ is uniformly distributed over $0,1,2,3$ and $X$ and $Y$ are also uniformly distributed over $0,2$ and $0,1$. Therefore it is easy to see that $H(Z)=H(X)+H(Y)$.






            share|cite|improve this answer




















            • I like your example +1
              – Ahmad Bazzi
              Sep 8 at 20:55












            up vote
            2
            down vote










            up vote
            2
            down vote









            To construct a proper example, as you found out yourself in a very nice fashion, there is a bijection between $Z$ and $(X,Y)$ (I suppose that random variables are discrete of course).



            Let $X'sim textBernoulli(frac 12)$ and $Ysim textBernoulli(frac 12)$. Set $X=2X'$ and take $Z=X+Y$. Then $Z$ is uniformly distributed over $0,1,2,3$ and $X$ and $Y$ are also uniformly distributed over $0,2$ and $0,1$. Therefore it is easy to see that $H(Z)=H(X)+H(Y)$.






            share|cite|improve this answer












            To construct a proper example, as you found out yourself in a very nice fashion, there is a bijection between $Z$ and $(X,Y)$ (I suppose that random variables are discrete of course).



            Let $X'sim textBernoulli(frac 12)$ and $Ysim textBernoulli(frac 12)$. Set $X=2X'$ and take $Z=X+Y$. Then $Z$ is uniformly distributed over $0,1,2,3$ and $X$ and $Y$ are also uniformly distributed over $0,2$ and $0,1$. Therefore it is easy to see that $H(Z)=H(X)+H(Y)$.







            share|cite|improve this answer












            share|cite|improve this answer



            share|cite|improve this answer










            answered Sep 8 at 20:16









            Arash

            9,53821537




            9,53821537











            • I like your example +1
              – Ahmad Bazzi
              Sep 8 at 20:55
















            • I like your example +1
              – Ahmad Bazzi
              Sep 8 at 20:55















            I like your example +1
            – Ahmad Bazzi
            Sep 8 at 20:55




            I like your example +1
            – Ahmad Bazzi
            Sep 8 at 20:55










            up vote
            1
            down vote













            In addition to the nice example @Arash gives. Assume the discrete uniform distribution. If $$X sim mathcal U_[a,b](n)$$and$$Y sim mathcal U_[c,d](m)$$
            Let's define $$Z = X+Y$$
            We know that the entropies of $X$ and $Y$ are $$H(X) = log n$$ and $$H(Y) = log m$$ therefore $$H(X) + H(Y) = log(n) + log(m) = log(nm)$$
            This means that if $Z$ has $nm$ outcomes, then we can assert that $H(Z) = H(X) + H(Y)$. Many examples could be generated here to demonstrate the need of being bijective.



            One Example out of MANY



            Assume $X in lbrace 1,2,3rbrace$ and $Y in lbrace 0,10,20 rbrace$. It is easy to see that $$Z in lbrace 1,2,3,11,12,13,21,22,23 rbrace$$ with $$P(Z = z) = frac19$$
            Is $H(Z) = ln(3times 3) = log 9$ ? Of course, because we $X+Y$ here is bijective.



            Let's prove it: $$H(Z) = sumlimits_k=1^9 p_k log(frac1p_k) = sumlimits_k=1^9 frac19 log(9) =9frac19 log(9) = log(9)$$



            Counter example



            Now let's take the same distributions (with different outcomes) but show that $H(Z)$ will not reach $log(9)$ if there is no bijectivity. Let $X in lbrace 0,1,2 rbrace$ and $Y in lbrace 3,4,5 rbrace $. So $$Z in lbrace 3,4,5,6,7 rbrace$$
            Therefore, it is clear there is no bijectivity, because $(1,3)$ and $(0,4)$ both give $Z = 4$, hence we can not decode $X,Y$ from $Z$.
            Computing the entropy $$H(Z) = frac19 log 9 + frac29 log frac92 +frac39 log frac93 + frac29 log frac92 + frac19 log 9 < log(9)$$






            share|cite|improve this answer


























              up vote
              1
              down vote













              In addition to the nice example @Arash gives. Assume the discrete uniform distribution. If $$X sim mathcal U_[a,b](n)$$and$$Y sim mathcal U_[c,d](m)$$
              Let's define $$Z = X+Y$$
              We know that the entropies of $X$ and $Y$ are $$H(X) = log n$$ and $$H(Y) = log m$$ therefore $$H(X) + H(Y) = log(n) + log(m) = log(nm)$$
              This means that if $Z$ has $nm$ outcomes, then we can assert that $H(Z) = H(X) + H(Y)$. Many examples could be generated here to demonstrate the need of being bijective.



              One Example out of MANY



              Assume $X in lbrace 1,2,3rbrace$ and $Y in lbrace 0,10,20 rbrace$. It is easy to see that $$Z in lbrace 1,2,3,11,12,13,21,22,23 rbrace$$ with $$P(Z = z) = frac19$$
              Is $H(Z) = ln(3times 3) = log 9$ ? Of course, because we $X+Y$ here is bijective.



              Let's prove it: $$H(Z) = sumlimits_k=1^9 p_k log(frac1p_k) = sumlimits_k=1^9 frac19 log(9) =9frac19 log(9) = log(9)$$



              Counter example



              Now let's take the same distributions (with different outcomes) but show that $H(Z)$ will not reach $log(9)$ if there is no bijectivity. Let $X in lbrace 0,1,2 rbrace$ and $Y in lbrace 3,4,5 rbrace $. So $$Z in lbrace 3,4,5,6,7 rbrace$$
              Therefore, it is clear there is no bijectivity, because $(1,3)$ and $(0,4)$ both give $Z = 4$, hence we can not decode $X,Y$ from $Z$.
              Computing the entropy $$H(Z) = frac19 log 9 + frac29 log frac92 +frac39 log frac93 + frac29 log frac92 + frac19 log 9 < log(9)$$






              share|cite|improve this answer
























                up vote
                1
                down vote










                up vote
                1
                down vote









                In addition to the nice example @Arash gives. Assume the discrete uniform distribution. If $$X sim mathcal U_[a,b](n)$$and$$Y sim mathcal U_[c,d](m)$$
                Let's define $$Z = X+Y$$
                We know that the entropies of $X$ and $Y$ are $$H(X) = log n$$ and $$H(Y) = log m$$ therefore $$H(X) + H(Y) = log(n) + log(m) = log(nm)$$
                This means that if $Z$ has $nm$ outcomes, then we can assert that $H(Z) = H(X) + H(Y)$. Many examples could be generated here to demonstrate the need of being bijective.



                One Example out of MANY



                Assume $X in lbrace 1,2,3rbrace$ and $Y in lbrace 0,10,20 rbrace$. It is easy to see that $$Z in lbrace 1,2,3,11,12,13,21,22,23 rbrace$$ with $$P(Z = z) = frac19$$
                Is $H(Z) = ln(3times 3) = log 9$ ? Of course, because we $X+Y$ here is bijective.



                Let's prove it: $$H(Z) = sumlimits_k=1^9 p_k log(frac1p_k) = sumlimits_k=1^9 frac19 log(9) =9frac19 log(9) = log(9)$$



                Counter example



                Now let's take the same distributions (with different outcomes) but show that $H(Z)$ will not reach $log(9)$ if there is no bijectivity. Let $X in lbrace 0,1,2 rbrace$ and $Y in lbrace 3,4,5 rbrace $. So $$Z in lbrace 3,4,5,6,7 rbrace$$
                Therefore, it is clear there is no bijectivity, because $(1,3)$ and $(0,4)$ both give $Z = 4$, hence we can not decode $X,Y$ from $Z$.
                Computing the entropy $$H(Z) = frac19 log 9 + frac29 log frac92 +frac39 log frac93 + frac29 log frac92 + frac19 log 9 < log(9)$$






                share|cite|improve this answer














                In addition to the nice example @Arash gives. Assume the discrete uniform distribution. If $$X sim mathcal U_[a,b](n)$$and$$Y sim mathcal U_[c,d](m)$$
                Let's define $$Z = X+Y$$
                We know that the entropies of $X$ and $Y$ are $$H(X) = log n$$ and $$H(Y) = log m$$ therefore $$H(X) + H(Y) = log(n) + log(m) = log(nm)$$
                This means that if $Z$ has $nm$ outcomes, then we can assert that $H(Z) = H(X) + H(Y)$. Many examples could be generated here to demonstrate the need of being bijective.



                One Example out of MANY



                Assume $X in lbrace 1,2,3rbrace$ and $Y in lbrace 0,10,20 rbrace$. It is easy to see that $$Z in lbrace 1,2,3,11,12,13,21,22,23 rbrace$$ with $$P(Z = z) = frac19$$
                Is $H(Z) = ln(3times 3) = log 9$ ? Of course, because we $X+Y$ here is bijective.



                Let's prove it: $$H(Z) = sumlimits_k=1^9 p_k log(frac1p_k) = sumlimits_k=1^9 frac19 log(9) =9frac19 log(9) = log(9)$$



                Counter example



                Now let's take the same distributions (with different outcomes) but show that $H(Z)$ will not reach $log(9)$ if there is no bijectivity. Let $X in lbrace 0,1,2 rbrace$ and $Y in lbrace 3,4,5 rbrace $. So $$Z in lbrace 3,4,5,6,7 rbrace$$
                Therefore, it is clear there is no bijectivity, because $(1,3)$ and $(0,4)$ both give $Z = 4$, hence we can not decode $X,Y$ from $Z$.
                Computing the entropy $$H(Z) = frac19 log 9 + frac29 log frac92 +frac39 log frac93 + frac29 log frac92 + frac19 log 9 < log(9)$$







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited Sep 8 at 21:06

























                answered Sep 8 at 20:55









                Ahmad Bazzi

                6,4061624




                6,4061624












                    這個網誌中的熱門文章

                    How to combine Bézier curves to a surface?

                    Carbon dioxide

                    Why am i infinitely getting the same tweet with the Twitter Search API?