English

Efron's monotonicity property for measures on $\mathbb{R}^2$

Statistics Theory 2017-12-22 v2 Probability Statistics Theory

Abstract

First we prove some kernel representations for the covariance of two functions taken on the same random variable and deduce kernel representations for some functionals of a continuous one-dimensional measure. Then we apply these formulas to extend Efron's monotonicity property, given in Efron [1965] and valid for independent log-concave measures, to the case of general measures on R2\mathbb{R}^2. The new formulas are also used to derive some further quantitative estimates in Efron's monotonicity property.

Keywords

Cite

@article{arxiv.1707.04472,
  title  = {Efron's monotonicity property for measures on $\mathbb{R}^2$},
  author = {Adrien Saumard and Jon A. Wellner},
  journal= {arXiv preprint arXiv:1707.04472},
  year   = {2017}
}
R2 v1 2026-06-22T20:47:10.647Z