Let $X,Y$ and $Z$ be random vectors in $\mathbb{R}^d$ defined on $(\Omega,\mathcal{H},\mathsf{P})$ s.t. $Z$ is $\mathcal{F}$-measurable for some $\mathcal{F}\subset\mathcal{H}$. Define a family of random, convex, closed sets: $$ A_t(\omega):=\{x\in \mathbb{R}^d:x^{\top}Z(\omega)\le t\} $$ indexed by $t\in\mathbb{R}$. Is there a family of sets $\mathcal{C}\subset\mathcal{B}(\mathbb{R}^d)$ (independent of $Z$) s.t. for each $t\in \mathbb{R}$, \begin{align} &|\mathsf{P}(X\in A_t\mid\mathcal{F})-\mathsf{P}(Y\in A_t\mid \mathcal{F})| \\ &\qquad\le \operatorname{esssup_{C\in\mathcal{C}}}|\mathsf{P}(X\in C\mid\mathcal{F})-\mathsf{P}(Y\in C\mid \mathcal{F})| \quad\text{a.s.}? \end{align}
Probability bound involving random, convex sets
d.k.o.
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