Complete Convergence for Weighted Sums of -Mixing Random Variables

By Soo Hak Sung. 2010

69 citations recorded by the source corpus.

We obtain the complete convergence for weighted sums of -mixing random variables. Our result extends the result of Peligrad and Gut (1999) on unweighted average to a weighted average under a mild condition of weights. Our result also generalizes and sharpens the result of An and Yuan (2008).

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/754ce140488c997b07eed597e6c579198ead4638

How researchers see this paper

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

In Management Science and Operations Research

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Andrei Volodin
5. Chen Xu

In Statistics and Probability

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Chen Xu

Citations in the corpus

• Complete convergence for weighted sums of NSD random variables and its application in the EV regression model (2014, unknown): “For the details, one can refer to Spitzer (1956), Baum and Katz (1965), Wu (2010, 2012a, b), Sung (2010, 2012), Wang et al. (2012a, b), Shen et al. (2013a, b), and so forth.”
• On asymptotic approximation of inverse moments for a class of nonnegative random variables (2014, background): “See for example, φ mixing identically distributed random variables with ∑∞ n= φ1/2(2n) < ∞ (see [19]), ρ mixing identically distributed random variables with ∑∞ n= ρ2/p(2n) < ∞ (see [20]), negatively associated random variables (see [21]), ρ̃ mixing random variables (see [22]), negatively dependent ”
• On Complete Convergence for an Extended Negatively Dependent Sequence (2014, background): “The main idea is inspired by Sung (2010).”