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《中国高等学校学术文摘·数学》
>Complete moment convergence for weighted sums of widely orthant-dependent random variables and its application in nonparametric regression models
Complete moment convergence for weighted sums of widely orthant-dependent random variables and its application in nonparametric regression models
We establish some results on the complete moment convergence for weighted sums of widely orthant-dependent(WOD)random variables,which improve and extend the corresponding results of Y.F.Wu,M.G.Zhai,and J.Y.Peng[J.Math.Inequal.,2019,13(1):251–260].As an application of the main results,we investigate the complete consistency for the estimator in a nonparametric regression model based on WOD errors and provide some simulations to verify our theoretical results.
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机译:Complete q-th moment convergence for the maximum of partial sums of m-negatively associated random variables and its application to the EV regression model
机译:Complete moment convergence for randomly weighted sums of arrays of rowwise mndocumentclass12pt{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$$m_n$$end{document}-extended negatively dependent random variables and its applications