Complete Convergence for Negatively Dependent Sequences of Random Variables

By Qunying Wu. 2010

47 citations recorded by the source corpus.

We study the complete convergence for negatively dependent sequences of random variables. As a result, we extend some complete convergence theorems for independent random variables to the case of negatively dependent random variables without necessarily imposing any extra conditions.

Subfields: Finance, Management Science and Operations Research, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/58e8efa6eb2147b7d75dcb06ef967f4a274f288a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Wenzhi Yang

In Management Science and Operations Research

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Zhiyong Chen
5. Wenzhi Yang
6. Andrei Volodin
7. Chen Xu

In Mathematical Physics

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Wenzhi Yang

Citations in the corpus

• Complete convergence for arrays of rowwise negatively orthant dependent random variables (2011, background): “[16], Zareo and Jabbari [20] and Wu [18,19] for complete convergence, and so on.”
• Complete convergence for weighted sums of NSD random variables and its application in the EV regression model (2014, background): “For the proof, one can refer to Wu (2006), Shen (2013), Shen and Wu (2013), or Wang et al. (2014b) Lemma 2.6 Let {Xn, n ≥ 1} be an array of rowwise random variables which is stochastically dominated by a random variable X.”
• On the strong convergence rate for weighted sums of arrays of rowwise negatively orthant dependent random variables (2013, methodology): “We refer to [19] for the Kolmogorov exponential inequality, [4] for the Rosenthals type inequality, [11] for Hájek–Rényi type inequality, [2,3,12,13] for almost sure convergence, [1,14,15,18,21–23] for complete convergence, and so on.”