Intermediately trimmed sums of oppenheim expansions: A strong law

Abstract The work of this paper is devoted to obtaining strong laws for intermediately trimmed sums of random variables with infinite means. Particularly, we provide conditions under which the intermediately trimmed sums of independent but not identically distributed random variables converge almost surely. Moreover, by dropping the assumption of independence we provide a corresponding convergence result for a special class of Oppenheim expansions. We highlight that the results of this paper generalize the results provided in the recent work of [13] while the convergence of intermediately trimmed sums of generalized Oppenheim expansions is studied for the first time.

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Journal
Mathematica Slovaca
Published
2025-12-01
DOI
https://doi.org/10.1515/ms-2025-0109
Primary Topic
Probability and Risk Models
Type
article
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article

Intermediately trimmed sums of oppenheim expansions: A strong law

Milto Hadjikyriakou, Rita Giuliano
Mathematica Slovaca
Probability and Risk Models
article

Intermediately trimmed sums of oppenheim expansions: A strong law

Milto Hadjikyriakou, Rita Giuliano
article en

Abstract

Abstract The work of this paper is devoted to obtaining strong laws for intermediately trimmed sums of random variables with infinite means. Particularly, we provide conditions under which the intermediately trimmed sums of independent but not identically distributed random variables converge almost surely. Moreover, by dropping the assumption of independence we provide a corresponding convergence result for a special class of Oppenheim expansions. We highlight that the results of this paper generalize the results provided in the recent work of [13] while the convergence of intermediately trimmed sums of generalized Oppenheim expansions is studied for the first time.

Mathematica SlovacaVol. 75(6)
University of Pisa (IT), University of Central Lancashire Cyprus (CY), Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (IT)
Openalex Percentile: Top 55%
Probability and Risk Models
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