Complete moment convergence for arrays of rowwise widely orthant dependent random variables
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Publication:1633832
DOI10.1007/s10114-018-7173-zzbMath1404.60041OpenAlexW2804296734MaRDI QIDQ1633832
Yi Wu, Andrew Rosalsky, Xue-jun Wang
Publication date: 21 December 2018
Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10114-018-7173-z
complete convergencecomplete moment convergencearray of widely orthant dependent random variablescomplete integral convergence
Related Items (13)
Convergence properties for the partial sums of widely orthant dependent random variables under some integrable assumptions and their applications ⋮ Convergence rates in the law of large numbers and new kinds of convergence of random variables ⋮ Complete moment convergence for the widely orthant dependent linear processes with random coefficients ⋮ Complete and complete integral convergence for arrays of row wise widely negative dependent random variables under the sub-linear expectations ⋮ Complete integral convergence for weighted sums of widely negative dependent random variables under the sub-linear expectations ⋮ Complete convergence for randomly weighted sums of random variables and its application in linear-time-invariant systems ⋮ Strong consistency of least-squares estimators in the simple linear errors-in-variables regression model with widely orthant dependent random variables ⋮ Laws of large numbers and complete convergence for WOD random variables and their applications ⋮ Complete moment convergence for weighted sums of widely orthant-dependent random variables and its application in nonparametric regression models ⋮ Complete \(f\)-moment convergence for widely orthant dependent random variables and its application in nonparametric models ⋮ Consistency of the Priestley-Chao estimator in nonparametric regression model with widely orthant dependent errors ⋮ Complete and complete integral convergence for weighted sums of arrays of rowwise widely negative dependent random variables under the sub-linear expectations ⋮ Complete f-moment convergence of moving average process and its application to nonparametric regression models
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