The question I have is:
Define X,Y to be two independent uniform(0,1) random variables and $Z:=\frac{Y}{X}$
Compute $P(X<x|\sigma(Z))$
The answer given apparently by "straightforward elementary computations" is for $x\geq 0$
$P(X<x|\sigma(Z))$=min$\{{x^2,1}\}\mathbb{I}_{Z\leq 1}$ $+$ min$\{{x^2 Z^2,1}\}\mathbb{I}_{Z\geq 1}$.
My idea was to condition on the $Z\leq 1$ and ${Z\geq 1}$ then compute using the joint density of X and Y, but this seems to work for the first term but doesn't for the second? Any help would be much appreciated.