Almost Sure Convergence Theorem and Strong Stability for Weighted Sums of NSD Random Variables

Almost Sure Convergence Theorem and Strong Stability for Weighted Sums of NSD Random Variables

In this paper, Kolmogorov-type inequality for negatively superadditive dependent （NSD） random variables is established. By using this inequality, we obtain the almost sure convergence for NSD sequences, which extends the corresponding results for independent sequences and negatively associated （NA）...

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Veröffentlicht in:Acta mathematica Sinica. English series 2013-04, Vol.29 (4), p.743-756
Hauptverfasser: Shen, Yan, Wang, Xue Jun, Yang, Wen Zhi, Hu, Shu He
Format: Artikel
Sprache:eng
Schlagworte:
Algebra
Codes
Convergence
Inequalities
Inequality
Mathematics
Mathematics and Statistics
NSD
Random variables
SD序列
Stability
Studies
Sums
Theorems
几乎处处收敛
加权和
收敛定理
柯尔莫哥洛夫
稳定性
随机变量
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Beschreibung
Zusammenfassung:In this paper, Kolmogorov-type inequality for negatively superadditive dependent （NSD） random variables is established. By using this inequality, we obtain the almost sure convergence for NSD sequences, which extends the corresponding results for independent sequences and negatively associated （NA） sequences. In addition, the strong stability for weighted sums of NSD random variables is studied.
ISSN:1439-8516
1439-7617
DOI:10.1007/s10114-012-1723-6