Complete convergence for weighted sums of i.i.d. random variables with applications in regression estimation and EV model. Issue 7 (3rd April 2017)

• Record Type: Journal Article
• Authors: Chen, Pingyan; Kong, Ningning; Sung, Soo Hak
• Is Part Of: Communications in statistics. Volume 46:Issue 7(2017)
• Page Start: 3599
• Page End: 3613
• Publication Date: 2017-04-03
• Subjects: Complete convergence -- EV model -- regression -- strong law -- weighted sums; Primary 60F15 -- Secondary 62G05; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2015.1066817
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: In this paper, we obtain complete convergence results for Stout type weighted sums of i.i.d. random variables. A strong law for weighted sums of i.i.d. random variables is also obtained. As the applications of the strong law, the strong consistency and rate of the nonparametric regression estimations and the rates of the strong consistency of LS estimators for the unknown parameters of the simple linear errors in variables (EV) model are given.