Complete moment convergence of moving-average processes under END assumptions
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Publication:5081069
DOI10.1080/03610926.2020.1767138OpenAlexW3027905406MaRDI QIDQ5081069
Publication date: 1 June 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2020.1767138
Cites Work
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- Probability inequalities for END sequence and their applications
- Large deviations for some weakly dependent random processes
- Necessary and sufficient conditions for moderate deviations of dependent random variables with heavy tails
- Precise large deviations for dependent random variables with heavy tails
- Complete convergence of moving average processes
- Complete moment convergence of moving-average processes under dependence assumptions
- Complete convergence for Sung's type weighted sums of END random variables
- Central limit theorems for moving average processes
- Exponential probability inequality for \(m\)-END random variables and its applications
- Complete convergence for weighted sums of END random variables and its application to nonparametric regression models
- The Strong Law of Large Numbers for Extended Negatively Dependent Random Variables
- CONVERGENCE PROPERTIES OF THE PARTIAL SUMS FOR SEQUENCES OF END RANDOM VARIABLES
- ON THE COMPLETE CONVERGENCE FOR ARRAYS OF ROWWISE EXTENDED NEGATIVELY DEPENDENT RANDOM VARIABLES
- Berry-Esseen type bounds of the estimators in a semiparametric model under linear process errors with α-mixing dependent innovations
- A general result on complete convergence for weighted sums of linear processes and its statistical applications
- Complete convergence and complete moment convergence for arrays of rowwise END random variables
- Some Limit Theorems for Stationary Processes
- Complete Convergence and the Law of Large Numbers
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