On the Strong Law of Large Numbers for Nonidentically Distributed, Partially Dependent Random Variables

Abstract A new version of the strong law of large numbers is proposed for a “good” sequence of pairwise independent random variables (r.v.’s) with a small portion of “bad” dependent r.v.’s. The main goal was to weaken the requirement for the existence of the expectation for each term: the r.v.’s of the bad, “sparse” part of the sequence may have moments of orders converging to zero.

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Publication Details

Journal
Mathematical Notes
Published
2026-09-30
DOI
https://doi.org/10.1134/s000143462660434x
Primary Topic
Probability and Risk Models
Type
article
Field-Weighted Citation Impact
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On the Strong Law of Large Numbers for Nonidentically Distributed, Partially Dependent Random Variables

A. Yu. Veretennikov, I. V. Kozlov
Mathematical Notes
Probability and Risk Models
article

On the Strong Law of Large Numbers for Nonidentically Distributed, Partially Dependent Random Variables

A. Yu. Veretennikov, I. V. Kozlov
article en

Abstract

Abstract A new version of the strong law of large numbers is proposed for a “good” sequence of pairwise independent random variables (r.v.’s) with a small portion of “bad” dependent r.v.’s. The main goal was to weaken the requirement for the existence of the expectation for each term: the r.v.’s of the bad, “sparse” part of the sequence may have moments of orders converging to zero.

Mathematical NotesVol. 120(5-6)
Peoples' Friendship University of Russia (RU), Lomonosov Moscow State University (RU), Institute for Information Transmission Problems (RU)
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
Probability and Risk Models
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