A Note on the Gaussian Minimum Conjecture

preprint2020arXivOpen access

Abstract

Let n≥2n\geq 2 and (Xi,1≤i≤n)(X_i,1\leq i\leq n) be a centered Gaussian random vector. The Gaussian minimum conjecture says that E(min⁡1≤i≤n∣Xi∣)≥E(min⁡1≤i≤n∣Yi∣)E\left(\min_{1\leq i\leq n}|X_i|\right)\geq E\left(\min_{1\leq i\leq n}|Y_i|\right), where Y1,…,YnY_1,\ldots,Y_n are independent centered Gaussian random variables with E(Xi2)=E(Yi2)E(X_i^2)=E(Y_i^2) for any i=1,…,ni=1,\ldots,n. In this note, we will show that this conjecture holds if and only if n=2n=2.

Explore this paper’s authors, topics and related work.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Reviews 0

Write a reviewWrite

No reviews yet.

Discussion 0

Add a commentWrite

No comments yet.