A Strong Limit Theorem for Weighted Sums of Negatively Dependent Random Variables
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Publication:5249199
DOI10.1080/03610926.2012.742111zbMath1312.60025OpenAlexW2093118884MaRDI QIDQ5249199
Publication date: 29 April 2015
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2012.742111
complete convergencealmost sure convergenceweighted sumsstrong limit theoremnegatively dependent random variables
Related Items (2)
Some types of convergence for negatively dependent random variables under sublinear expectations ⋮ Complete convergence and complete moment convergence for arrays of rowwise negatively dependent random variables under sub-linear expectations
Cites Work
- Complete convergence for weighted sums of negatively dependent random variables
- Strong limit theorems for weighted sums of negatively associated random variables
- A remark on almost sure convergence of weighted sums
- Negative association of random variables, with applications
- A strong law for weighted sums of i.i.d. random variables
- Marcinkiewicz strong laws for linear statistics
- Limiting behavior of weighted sums of i.i.d. random variables
- A strong law of large numbers for arrays of rowwise negatively dependent random variables
- Almost certain convergence in double arrays
- Almost sure convergence theorems of weighted sums of random variables
- Some Concepts of Dependence
- Complete Convergence and the Law of Large Numbers
- Strong laws for weighted sums of i. i. d. random variables
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