On consistency of least square estimators in the simple linear EV model with negatively orthant dependent errors

DOI10.1214/17-EJS1263zbMath1362.62051MaRDI QIDQ527078

Shuhe Hu, Xue-jun Wang

Publication date: 16 May 2017

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1492567401

zbMATH Keywords

weak consistencystrong consistencycomplete consistencynegatively orthant dependent random variablesEV regression model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Strong limit theorems (60F15)

Related Items (9)

Strong law of large numbers for weighted sums of random variables and its applications in EV regression models ⋮ Unnamed Item ⋮ Complete convergence and complete moment convergence for maximal randomly weighted sums of widely orthant-dependent random variables with applications ⋮ Complete $f$-Moment Convergence for Randomly Weighted Sums of Extended Negatively Dependent Random Variables and Its Statistical Application ⋮ Strong consistency of least-squares estimators in the simple linear errors-in-variables regression model with widely orthant dependent random variables ⋮ Complete \(f\)-moment convergence for maximal randomly weighted sums of arrays of rowwise widely orthant dependent random variables and its statistical applications ⋮ Complete moment convergence for weighted sums of widely orthant-dependent random variables and its application in nonparametric regression models ⋮ Strong consistency of LS estimator in simple linear EV regression models ⋮ Strong and weak consistency of least squares estimators in simple linear EV regression models

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