Cantelli's bounds for generalized tail inequalities in Euclidean spaces

Abstract

Let $X$ be a centered random vector in a finite dimensional real inner product space $\mathcal{E}$. For a subset $C$ of the ambient vector space $V$ of $\mathcal{E}$ and $x,y\in V$, write $x{⪯}_{C}y$ if $y-x\in C$. When $C$ is a closed convex cone in $\mathcal{E}$, then ${⪯}_C$ is a pre-order on $V$, whereas if $C$ is a proper cone in $\mathcal{E}$, then ${⪯}_C$ is actually a partial order on $V$. In this paper we give sharp Cantelli's type inequalities for generalized tail probabilities like $\text{Pr}\{X{⪰}_{C}b\}$ for $b\in V$. These inequalities are obtained by ``scalarizing'' $X{⪰}_{C}b$ via cone duality and then by minimizing the classical univariate Cantelli's bound over the scalarized inequalities.