Expectation of log-density with respect to a different random variable












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Let $X$ and $Y$ be two continuous random variables with marginal density functions $f_{X}(x) $ and $f_{Y}(y) $.



Is it true that $$ E[log f_{X}(X)] geq E[log f_{Y}(X)] ?$$



Perhaps the concavity of the log function will come in handy, along with Jensen's inequality, but I am having particular trouble manipulating the $ f_{Y}(X) $ term.










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$endgroup$

















    1












    $begingroup$


    Let $X$ and $Y$ be two continuous random variables with marginal density functions $f_{X}(x) $ and $f_{Y}(y) $.



    Is it true that $$ E[log f_{X}(X)] geq E[log f_{Y}(X)] ?$$



    Perhaps the concavity of the log function will come in handy, along with Jensen's inequality, but I am having particular trouble manipulating the $ f_{Y}(X) $ term.










    share|cite|improve this question











    $endgroup$















      1












      1








      1





      $begingroup$


      Let $X$ and $Y$ be two continuous random variables with marginal density functions $f_{X}(x) $ and $f_{Y}(y) $.



      Is it true that $$ E[log f_{X}(X)] geq E[log f_{Y}(X)] ?$$



      Perhaps the concavity of the log function will come in handy, along with Jensen's inequality, but I am having particular trouble manipulating the $ f_{Y}(X) $ term.










      share|cite|improve this question











      $endgroup$




      Let $X$ and $Y$ be two continuous random variables with marginal density functions $f_{X}(x) $ and $f_{Y}(y) $.



      Is it true that $$ E[log f_{X}(X)] geq E[log f_{Y}(X)] ?$$



      Perhaps the concavity of the log function will come in handy, along with Jensen's inequality, but I am having particular trouble manipulating the $ f_{Y}(X) $ term.







      probability-theory inequality expectation






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      edited Jan 21 '18 at 23:26









      zoli

      17.1k41945




      17.1k41945










      asked Jan 21 '18 at 15:26









      E WernerE Werner

      655




      655






















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          $begingroup$

          By Jensen's inequality,
          $$
          mathsf{E}log frac{f_Y(X)}{f_X(X)}le log mathsf{E}frac{f_Y(X)}{f_X(X)}=log int frac{f_Y(x)}{f_X(x)}f_X(x)dx=0
          $$






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            $begingroup$

            By Jensen's inequality,
            $$
            mathsf{E}log frac{f_Y(X)}{f_X(X)}le log mathsf{E}frac{f_Y(X)}{f_X(X)}=log int frac{f_Y(x)}{f_X(x)}f_X(x)dx=0
            $$






            share|cite|improve this answer









            $endgroup$


















              1












              $begingroup$

              By Jensen's inequality,
              $$
              mathsf{E}log frac{f_Y(X)}{f_X(X)}le log mathsf{E}frac{f_Y(X)}{f_X(X)}=log int frac{f_Y(x)}{f_X(x)}f_X(x)dx=0
              $$






              share|cite|improve this answer









              $endgroup$
















                1












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                1





                $begingroup$

                By Jensen's inequality,
                $$
                mathsf{E}log frac{f_Y(X)}{f_X(X)}le log mathsf{E}frac{f_Y(X)}{f_X(X)}=log int frac{f_Y(x)}{f_X(x)}f_X(x)dx=0
                $$






                share|cite|improve this answer









                $endgroup$



                By Jensen's inequality,
                $$
                mathsf{E}log frac{f_Y(X)}{f_X(X)}le log mathsf{E}frac{f_Y(X)}{f_X(X)}=log int frac{f_Y(x)}{f_X(x)}f_X(x)dx=0
                $$







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                share|cite|improve this answer



                share|cite|improve this answer










                answered Jan 2 at 3:20









                d.k.o.d.k.o.

                10.6k730




                10.6k730






























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