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An Opposite Gaussian Product Inequality

Probability 2022-05-23 v1

Abstract

The long-standing Gaussian product inequality (GPI) conjecture states that E[j=1nXjαj]j=1nE[Xjαj]E [\prod_{j=1}^{n}|X_j|^{\alpha_j}]\geq\prod_{j=1}^{n}E[|X_j|^{\alpha_j}] for any centered Gaussian random vector (X1,,Xn)(X_1,\dots,X_n) and any non-negative real numbers αj\alpha_j, j=1,,nj=1,\ldots,{n}. In this note, we prove a novel "opposite GPI" for centered bivariate Gaussian random variables when 1<α1<0-1<\alpha_1<0 and α2>0\alpha_2>0: E[X1α1X2α2]E[X1α1]E[X2α2]E[|X_1|^{\alpha_1}|X_2|^{\alpha_2}]\le E[|X_1|^{\alpha_1}]E[|X_2|^{\alpha_2}]. This completes the picture of bivariate Gaussian product relations.

Keywords

Cite

@article{arxiv.2205.10231,
  title  = {An Opposite Gaussian Product Inequality},
  author = {Oliver Russell and Wei Sun},
  journal= {arXiv preprint arXiv:2205.10231},
  year   = {2022}
}
R2 v1 2026-06-24T11:23:35.433Z