A paradox in least-squares estimation of linear regression models

DOI10.1016/S0167-7152(98)00205-3zbMath0913.62057OpenAlexW1989860523MaRDI QIDQ1284063

Mei-Hui Guo, Zhi-Dong Bai

Publication date: 10 June 1999

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-7152(98)00205-3

zbMATH Keywords

consistencyleast-squares estimatorrth moment

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05)

Related Items (4)

Maximum likelihood estimators in linear regression models with Ornstein-Uhlenbeck process ⋮ Hypothesis testing in generalized linear models with functional coefficient autoregressive pro\-cesses ⋮ The mean-variance ratio test -- a complement to the coefficient of variation test and the Sharpe ratio test ⋮ QML estimators in linear regression models with functional coefficient autoregressive processes

Cites Work

• Unnamed Item
• Strong consistency of least squares estimates in multiple regression II
• Convergence systems and strong consistency of least squares estimates in regression models
• Abnormal behavior of the least squares estimate of multiple regression
• Weak and strong consistency of the least squares estimators in regression models

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