Inference for nested error linear regression models with unequal error variances

DOI10.1016/S0378-3758(00)00081-1zbMath0954.62086OpenAlexW1970976123MaRDI QIDQ1580000

J. N. K. Rao, M. Yu

Publication date: 18 February 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(00)00081-1

zbMATH Keywords

simulationsvariance componentstwo-step estimatorapproximate MINQUEdelete-group jackknifejackknife inference

Mathematics Subject Classification ID

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

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Cites Work

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• Asymptotic distribution of the weighted least squares estimator
• Consistency and asymptotic normality of the maximum likelihood estimator in generalized linear models
• Estimation for a linear regression model with unknown diagonal covariance matrix
• Variance components of the linear regression model with a random intercept
• Estimating the Common Mean of Possibly Different Normal Populations: A Simulation Study
• Estimators for the One-Way Random Effects Model with Unequal Error Variances
• Jackknife inference for heteroscedastic linear regression models
• The Unbiasedness of Zellner's Seemingly Unrelated Regression Equations Estimators
• Linear Statistical Inference and its Applications
• The Combination of Estimates from Different Experiments

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