Complete Convergence and Complete Moment Convergence for Randomly Weighted Sums of Widely Negative Dependent Random Variables under Sublinear Expectations
It is well known that the convergence properties for weighted sums of random variables are important topics in probability limit theory. In this paper, under some suitable conditions, we study the complete convergence and complete moment convergence for randomly weighted sums of arrays of rowwise widely negative dependent random variables in sublinear expectation space, which extend the corresponding ones in classical probability space to the case of sublinear expectation space. As an application, we obtain strong law of large numbers for the randomly weighted sums of arrays of rowwise widely negative dependent random variables.
Authors
- M. M. Wang
- Xiaomeng Wang (ORCID: https://orcid.org/0000-0001-8319-440X)
Publication Details
- Journal
- Theory of Probability and Its Applications
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1137/s0040585x97t99246x
- Primary Topic
- Probability and Risk Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00