Efron's monotonicity property for measures on $\mathbb{R}^2$
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 $\mathbb{R}^2$. The new formulas are also used to derive some further quantitative estimates in Efron's monotonicity property.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2017
- DOI:
- arXiv:
- arXiv:1707.04472
- Bibcode:
- 2017arXiv170704472S
- Keywords:
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- Mathematics - Statistics Theory;
- Mathematics - Probability;
- 60E15;
- 60F10