Strong law of large numbers for $φ$-sub-Gaussian random variables under sub-linear expectation spaces

Fuente: arXiv
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Main Authors: Masasila, Nyanga Honda, Fazekas, István
Format: Preprint
Published: 2026
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author Masasila, Nyanga Honda
Fazekas, István
author_facet Masasila, Nyanga Honda
Fazekas, István
contents We introduce the notions of sub Gaussian random variables in sub-linear expectation spaces. To avoid the problem caused by the existence of two different expectations, i.e., the upper expectation and the lower expectation, we divide the definition of the sub-Gaussian property into an upper part and a lower part. It turns out that this approach fits well to the sub-linear setting; it provides a proper framework for extending Zajkowski's general result to sublinear expectation spaces. Within our framework, we establish a strong law of large numbers for sub-Gaussian sequences. We present an example showing the usefulness of our results.
format Preprint
id arxiv_https___arxiv_org_abs_2602_18175
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Strong law of large numbers for $φ$-sub-Gaussian random variables under sub-linear expectation spaces
Masasila, Nyanga Honda
Fazekas, István
Probability
We introduce the notions of sub Gaussian random variables in sub-linear expectation spaces. To avoid the problem caused by the existence of two different expectations, i.e., the upper expectation and the lower expectation, we divide the definition of the sub-Gaussian property into an upper part and a lower part. It turns out that this approach fits well to the sub-linear setting; it provides a proper framework for extending Zajkowski's general result to sublinear expectation spaces. Within our framework, we establish a strong law of large numbers for sub-Gaussian sequences. We present an example showing the usefulness of our results.
title Strong law of large numbers for $φ$-sub-Gaussian random variables under sub-linear expectation spaces
topic Probability
url https://arxiv.org/abs/2602.18175