How to find which of two events -drawn from a normal distribution- is more likely?












1












$begingroup$


I know the probability of event A is given by:



$$Phi(f(x)+g(y)) - Phi(f(x)-g(y)), $$



and the probability of event B is



$$Phi(m(y)+n(x)) - Phi(m(y)-n(x)).$$
where $Phi$ is the cumulative distribution function of the standard normal.



I want to find the more likely of those two events as a function of $x$ and $y$. I tried a few different approaches, but I couldn't make it much simpler than this:



$$Pr(A|x,y) > Pr(B|x,y)
\ Leftrightarrow frac{1}{2 pi} intlimits_{ f(x) - g(y) }^{f(x) + g(y) } e^{-t^2/2} dt > frac{1}{2 pi} intlimits_{ m(y) - n(x) }^{ m(y) + n(x) } e^{-t^2/2} dt $$



An obvious sufficient condition for $Pr(A|x,y) > Pr(B|x,y)$ is $f(x) - g(y) < m(y) - n(x)$ and $f(x) + g(y) > m(y) + n(x)$. But I can't figure out a tractable necessary condition. I would appreciate any hints!



Edit: I can assume that $f$ and $m$ are linear, and $g$ and $n$ quadratic, if that is of any use.










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$endgroup$

















    1












    $begingroup$


    I know the probability of event A is given by:



    $$Phi(f(x)+g(y)) - Phi(f(x)-g(y)), $$



    and the probability of event B is



    $$Phi(m(y)+n(x)) - Phi(m(y)-n(x)).$$
    where $Phi$ is the cumulative distribution function of the standard normal.



    I want to find the more likely of those two events as a function of $x$ and $y$. I tried a few different approaches, but I couldn't make it much simpler than this:



    $$Pr(A|x,y) > Pr(B|x,y)
    \ Leftrightarrow frac{1}{2 pi} intlimits_{ f(x) - g(y) }^{f(x) + g(y) } e^{-t^2/2} dt > frac{1}{2 pi} intlimits_{ m(y) - n(x) }^{ m(y) + n(x) } e^{-t^2/2} dt $$



    An obvious sufficient condition for $Pr(A|x,y) > Pr(B|x,y)$ is $f(x) - g(y) < m(y) - n(x)$ and $f(x) + g(y) > m(y) + n(x)$. But I can't figure out a tractable necessary condition. I would appreciate any hints!



    Edit: I can assume that $f$ and $m$ are linear, and $g$ and $n$ quadratic, if that is of any use.










    share|cite|improve this question











    $endgroup$















      1












      1








      1





      $begingroup$


      I know the probability of event A is given by:



      $$Phi(f(x)+g(y)) - Phi(f(x)-g(y)), $$



      and the probability of event B is



      $$Phi(m(y)+n(x)) - Phi(m(y)-n(x)).$$
      where $Phi$ is the cumulative distribution function of the standard normal.



      I want to find the more likely of those two events as a function of $x$ and $y$. I tried a few different approaches, but I couldn't make it much simpler than this:



      $$Pr(A|x,y) > Pr(B|x,y)
      \ Leftrightarrow frac{1}{2 pi} intlimits_{ f(x) - g(y) }^{f(x) + g(y) } e^{-t^2/2} dt > frac{1}{2 pi} intlimits_{ m(y) - n(x) }^{ m(y) + n(x) } e^{-t^2/2} dt $$



      An obvious sufficient condition for $Pr(A|x,y) > Pr(B|x,y)$ is $f(x) - g(y) < m(y) - n(x)$ and $f(x) + g(y) > m(y) + n(x)$. But I can't figure out a tractable necessary condition. I would appreciate any hints!



      Edit: I can assume that $f$ and $m$ are linear, and $g$ and $n$ quadratic, if that is of any use.










      share|cite|improve this question











      $endgroup$




      I know the probability of event A is given by:



      $$Phi(f(x)+g(y)) - Phi(f(x)-g(y)), $$



      and the probability of event B is



      $$Phi(m(y)+n(x)) - Phi(m(y)-n(x)).$$
      where $Phi$ is the cumulative distribution function of the standard normal.



      I want to find the more likely of those two events as a function of $x$ and $y$. I tried a few different approaches, but I couldn't make it much simpler than this:



      $$Pr(A|x,y) > Pr(B|x,y)
      \ Leftrightarrow frac{1}{2 pi} intlimits_{ f(x) - g(y) }^{f(x) + g(y) } e^{-t^2/2} dt > frac{1}{2 pi} intlimits_{ m(y) - n(x) }^{ m(y) + n(x) } e^{-t^2/2} dt $$



      An obvious sufficient condition for $Pr(A|x,y) > Pr(B|x,y)$ is $f(x) - g(y) < m(y) - n(x)$ and $f(x) + g(y) > m(y) + n(x)$. But I can't figure out a tractable necessary condition. I would appreciate any hints!



      Edit: I can assume that $f$ and $m$ are linear, and $g$ and $n$ quadratic, if that is of any use.







      inequality probability-distributions normal-distribution functional-inequalities






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      edited Dec 4 '18 at 22:56







      deanavery

















      asked Dec 3 '18 at 23:14









      deanaverydeanavery

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