On the ($$\boldsymbol{p,q}$$)-Type Strong Law of Large Numbers for Sequences of Pairwise Independent Random Vectors in Hilbert Spaces

The $$(p,q)$$ -type strong law of large numbers was studied by Li, Qi, and Rosalsky (Trans. Amer. Math. Soc., 2016) and Thành (Math. Nachr., 2023) for independent Banach space-valued random elements. This paper provides sufficient conditions for the $$(p,q)$$ -type strong law of large numbers for sequences of pairwise independent random vectors in Hilbert spaces. Although we assume only pairwise independence rather than mutual independence of the underlying random vectors, the sufficient conditions are only slightly stronger than those in the aforementioned works.

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Journal
Lobachevskii Journal of Mathematics
Published
2025-10-01
DOI
https://doi.org/10.1134/s1995080225610185
Primary Topic
Probability and Risk Models
Type
article
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article

On the ($$\boldsymbol{p,q}$$)-Type Strong Law of Large Numbers for Sequences of Pairwise Independent Random Vectors in Hilbert Spaces

Phuong Nguyen Thi Huyen, Trang Van Thi Quynh, Anh Ta Quynh
Lobachevskii Journal of Mathematics
Probability and Risk Models
article

On the ($$\boldsymbol{p,q}$$)-Type Strong Law of Large Numbers for Sequences of Pairwise Independent Random Vectors in Hilbert Spaces

Phuong Nguyen Thi Huyen, Trang Van Thi Quynh, Anh Ta Quynh
article en

Abstract

The $$(p,q)$$ -type strong law of large numbers was studied by Li, Qi, and Rosalsky (Trans. Amer. Math. Soc., 2016) and Thành (Math. Nachr., 2023) for independent Banach space-valued random elements. This paper provides sufficient conditions for the $$(p,q)$$ -type strong law of large numbers for sequences of pairwise independent random vectors in Hilbert spaces. Although we assume only pairwise independence rather than mutual independence of the underlying random vectors, the sufficient conditions are only slightly stronger than those in the aforementioned works.

Lobachevskii Journal of MathematicsVol. 46(10)
Vinh University (VN)
Peace, Justice and strong institutions
Openalex Percentile: Top 20%
Probability and Risk Models
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