Strong laws for randomly weighted sums of random variables and applications in the bootstrap and random design regression

DOI10.5705/ss.202017.0106zbMath1439.60032OpenAlexW2782126570MaRDI QIDQ5243734

Tao Zhang, Soo Hak Sung, Ping Yan Chen

Publication date: 19 November 2019

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/827be10f960f0fbdbf2dc7918a404f5641ae0a47

zbMATH Keywords

Marcinkiewicz-Zygmund strong lawlaw of the single logarithmrandomly weighted sumbootstrap sample meanregression with random design

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Strong limit theorems (60F15)

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Sufficient and necessary conditions for the strong consistency of LS estimators in simple linear EV regression models ⋮ Strong convergence for weighted sums of widely orthant dependent random variables and applications ⋮ Complete moment convergence for m-ANA random variables and statistical applications ⋮ Strong consistency of LS estimators in simple linear EV regression models with WOD errors

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