Strong laws for weighted sums of m-extended negatively dependent random variables and its applications

• Published in: Journal of mathematical analysis and applications Vol. 494; no. 2; p. 124566
• Main Authors: Wu, Yi, Wang, Xuejun
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.02.2021
• Subjects: Complete convergence; Conditional Value-at-risk estimator; m-extended negatively dependent random variables; Multiple linear regression model; Quasi-renewal counting process; Strong consistency; Conditional Value-at-risk estimator; m-extended negatively dependent random variables; Complete convergence; Strong consistency; Multiple linear regression model; Quasi-renewal counting process

In this paper, the sufficient and necessary conditions for complete convergence and the Kolmogorov strong law of large numbers for weighted sums of m-extended negatively dependent random variables are presented. Some applications of the main results are also provided, including the weak and strong c...