Convex combinations of random variables stochastically dominate the parent for a new class of heavy-tailed distributions

Fuente: arXiv
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Autori principali: Arab, Idir, Lando, Tommaso, Oliveira, Paulo Eduardo
Natura: Preprint
Pubblicazione: 2024
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author Arab, Idir
Lando, Tommaso
Oliveira, Paulo Eduardo
author_facet Arab, Idir
Lando, Tommaso
Oliveira, Paulo Eduardo
contents Stochastic dominance of a random variable by a convex combination of its independent copies has recently been shown to hold within the relatively narrow class of distributions with concave odds function, and later extended to broader families of distributions. A simple consequence of this surprising result is that the sample mean can be stochastically larger than the underlying random variable. We show that a key property for this stochastic dominance result to hold is the subadditivity of the cumulative distribution function of the reciprocal of the random variable of interest, referred to as the inverted distribution. By studying relations and inclusions between the different classes for which the stochastic dominance was proved to hold, we show that our new class can significantly enlarge the applicability of the result, providing a relatively mild sufficient condition.
format Preprint
id arxiv_https___arxiv_org_abs_2411_14926
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convex combinations of random variables stochastically dominate the parent for a new class of heavy-tailed distributions
Arab, Idir
Lando, Tommaso
Oliveira, Paulo Eduardo
Probability
60E15, 91G70, 62P05
Stochastic dominance of a random variable by a convex combination of its independent copies has recently been shown to hold within the relatively narrow class of distributions with concave odds function, and later extended to broader families of distributions. A simple consequence of this surprising result is that the sample mean can be stochastically larger than the underlying random variable. We show that a key property for this stochastic dominance result to hold is the subadditivity of the cumulative distribution function of the reciprocal of the random variable of interest, referred to as the inverted distribution. By studying relations and inclusions between the different classes for which the stochastic dominance was proved to hold, we show that our new class can significantly enlarge the applicability of the result, providing a relatively mild sufficient condition.
title Convex combinations of random variables stochastically dominate the parent for a new class of heavy-tailed distributions
topic Probability
60E15, 91G70, 62P05
url https://arxiv.org/abs/2411.14926