Central limit theorems for LS estimators in the EV regression model with dependent measure\-ments

DOI10.1016/j.jkss.2010.12.002zbMath1219.62044OpenAlexW2013709799MaRDI QIDQ634854

Juan-Miguel Gracia

Publication date: 17 August 2011

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2010.12.002

zbMATH Keywords

asymptotic normalitymartingale differences\(\alpha \)-mixing\(m\)-dependent\(\phi\)-mixing\(\rho \)-mixing

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Central limit and other weak theorems (60F05)

Related Items (5)

Asymptotic properties of LS estimator in nonlinear functional EV models ⋮ Consistency for the LS estimator in the linear EV regression model with replicate observations ⋮ Complete convergence of weighted sums of martingale differences and statistical applications ⋮ Consistency of LS estimators in the EV regression model with martingale difference errors ⋮ Asymptotic normality of Huber-Dutter estimators in a linear EV model with AR(1) processes

Cites Work

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• On the central limit theorem for sums of dependent random variables
• Convergence of stochastic processes

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