A general result on the strong convergence rate and complete convergence for arrays of rowwise extended negatively dependent random variables is established. As applications, some well-known results on negatively depe...A general result on the strong convergence rate and complete convergence for arrays of rowwise extended negatively dependent random variables is established. As applications, some well-known results on negatively dependent random variables can be easily extended to the case of arrays of rowwise extended negatively dependent random variables.展开更多
By using Rosenthal type moment inequality for extended negatively de- pendent random variables, we establish the equivalent conditions of complete convergence for weighted sums of sequences of extended negatively depe...By using Rosenthal type moment inequality for extended negatively de- pendent random variables, we establish the equivalent conditions of complete convergence for weighted sums of sequences of extended negatively dependent random variables under more general conditions. These results complement and improve the corresponding results obtained by Li et al. （Li D L, RAO M B, Jiang T F, Wang X C. Complete convergence and almost sure convergence of weighted sums of random variables. J. Theoret. Probab., 1995, 8： 49-76） and Liang （Liang H Y. Complete convergence for weighted sums of negatively associated random variables. Statist. Probab. Lett., 2000, 48： 317-325）.展开更多
In this paper, we establish a complete convergence result and a complete moment convergence result for weighted sums of widely orthant dependent random variables under mild conditions. As corollaries, the correspondin...In this paper, we establish a complete convergence result and a complete moment convergence result for weighted sums of widely orthant dependent random variables under mild conditions. As corollaries, the corresponding results for weighted sums of extended negatively orthant dependent random variables are also obtained, which generalize and improve the related known works in the literature.展开更多
In this paper,the complete convergence and the complete moment convergence for extended negatively dependent(END,in short) random variables without identical distribution are investigated.Under some suitable condition...In this paper,the complete convergence and the complete moment convergence for extended negatively dependent(END,in short) random variables without identical distribution are investigated.Under some suitable conditions,the equivalence between the moment of random variables and the complete convergence is established.In addition,the equivalence between the moment of random variables and the complete moment convergence is also proved.As applications,the Marcinkiewicz-Zygmund-type strong law of large numbers and the Baum-Katz-type result for END random variables are established.The results obtained in this paper extend the corresponding ones for independent random variables and some dependent random variables.展开更多
This paper mainly studies the strong convergence properties for weighted sums of extended negatively dependent(END,for short)random variables.Some sufficient conditions to prove the strong law of large numbers for wei...This paper mainly studies the strong convergence properties for weighted sums of extended negatively dependent(END,for short)random variables.Some sufficient conditions to prove the strong law of large numbers for weighted sums of END random variables are provided.In particular,the authors obtain the weighted version of Kolmogorov type strong law of large numbers for END random variables as a product.The results that the authors obtained generalize the corresponding ones for independent random variables and some dependent random variables.As an application,the authors investigate the errors-in-variables(EV,for short)regression models and establish the strong consistency for the least square estimators.Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real example is analysed for illustration.展开更多
In this paper, we investigate the complete moment convergence for dependent linear processes with random coefficients to form Xt =∑j^∞=∞ Aj∈t-j,where {∈n, n ∈ Z} is a sequence of END stochastically dominated ran...In this paper, we investigate the complete moment convergence for dependent linear processes with random coefficients to form Xt =∑j^∞=∞ Aj∈t-j,where {∈n, n ∈ Z} is a sequence of END stochastically dominated random variables and {An,n ∈ Z} is a sequence of random varibles. As applications, the convergence rate, Marcinkiewicz-Zvgmund strong law and strong law of large numbers for this linear process are established.展开更多
基金Supported by the National Natural Science Foundation of China（11201001） Supported by the Natural Science Foundation of Anhui Province（1208085QA03, 1308085QA03）+1 种基金 Supported by the Research Teaching Model Curriculum of Anhui University（xjyjkc1407） Supported by the Students Science Research Training Program of Anhui University（KYXL2014017）
Acknowledgement The authors are most grateful to the editor and anonymous referees for careful reading of the manuscript and valuable suggestions which helped in significantly improving an earlier version of this paper.
文摘A general result on the strong convergence rate and complete convergence for arrays of rowwise extended negatively dependent random variables is established. As applications, some well-known results on negatively dependent random variables can be easily extended to the case of arrays of rowwise extended negatively dependent random variables.
基金The NSF(11271020 and 11201004)of Chinathe NSF(10040606Q30 and 1208085MA11)of Anhui Provincethe NSF(KJ2012ZD01)of Education Department of Anhui Province
文摘By using Rosenthal type moment inequality for extended negatively de- pendent random variables, we establish the equivalent conditions of complete convergence for weighted sums of sequences of extended negatively dependent random variables under more general conditions. These results complement and improve the corresponding results obtained by Li et al. （Li D L, RAO M B, Jiang T F, Wang X C. Complete convergence and almost sure convergence of weighted sums of random variables. J. Theoret. Probab., 1995, 8： 49-76） and Liang （Liang H Y. Complete convergence for weighted sums of negatively associated random variables. Statist. Probab. Lett., 2000, 48： 317-325）.
基金Supported by National Natural Science Foundation of China(Grant No.11271161)
文摘In this paper, we establish a complete convergence result and a complete moment convergence result for weighted sums of widely orthant dependent random variables under mild conditions. As corollaries, the corresponding results for weighted sums of extended negatively orthant dependent random variables are also obtained, which generalize and improve the related known works in the literature.
基金supported by the National Natural Science Foundation of China(Nos.11501004,11501005,11526033)the Natural Science Foundation of Anhui Province(No.1508085J06)+4 种基金the Key Projects for Academic Talent of Anhui Province(No.gxbj ZD2016005)the Provincial Natural Science Research Project of Anhui Colleges(No.KJ2015A018)the Open Project of School of Mathematical Sciences,Anhui University(No.ADSY201503)the Quality Engineering Project of Anhui Province(No.2015jyxm045)the Quality Improvement Projects for Undergraduate Education of Anhui University(No.ZLTS2015035)
文摘In this paper,the complete convergence and the complete moment convergence for extended negatively dependent(END,in short) random variables without identical distribution are investigated.Under some suitable conditions,the equivalence between the moment of random variables and the complete convergence is established.In addition,the equivalence between the moment of random variables and the complete moment convergence is also proved.As applications,the Marcinkiewicz-Zygmund-type strong law of large numbers and the Baum-Katz-type result for END random variables are established.The results obtained in this paper extend the corresponding ones for independent random variables and some dependent random variables.
基金supported by the National Natural Science Foundation of China under Grant Nos.11671012 and 11871072the Natural Science Foundation of Anhui Province under Grant Nos.1808085QA03,1908085QA01,1908085QA07+1 种基金the Provincial Natural Science Research Project of Anhui Colleges under Grant No.KJ2019A0003the Students Innovative Training Project of Anhui University under Grant No.201910357002。
文摘This paper mainly studies the strong convergence properties for weighted sums of extended negatively dependent(END,for short)random variables.Some sufficient conditions to prove the strong law of large numbers for weighted sums of END random variables are provided.In particular,the authors obtain the weighted version of Kolmogorov type strong law of large numbers for END random variables as a product.The results that the authors obtained generalize the corresponding ones for independent random variables and some dependent random variables.As an application,the authors investigate the errors-in-variables(EV,for short)regression models and establish the strong consistency for the least square estimators.Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real example is analysed for illustration.
文摘In this paper, we investigate the complete moment convergence for dependent linear processes with random coefficients to form Xt =∑j^∞=∞ Aj∈t-j,where {∈n, n ∈ Z} is a sequence of END stochastically dominated random variables and {An,n ∈ Z} is a sequence of random varibles. As applications, the convergence rate, Marcinkiewicz-Zvgmund strong law and strong law of large numbers for this linear process are established.
