Minimum Variance Quadratic Unbiased Estimation for the Variance Components in Simple Linear Regression with Onefold Nested Error

DOI10.1080/03610920600692706zbMath1105.62073OpenAlexW1975125796MaRDI QIDQ3424160

Bilgehan Güven

Publication date: 15 February 2007

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920600692706

zbMATH Keywords

efficiencyvariance componentsasymptotically efficient estimatorMIVQUEANOVA estimatorinitial estimate

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (1)

Finite product representation via multiplicative calculus and its applications to exponential signal processing

Cites Work

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• Transformations for Estimation of Linear Models with Nested-Error Structure
• Monte Carlo Comparison of ANOVA, MIVQUE, REML, and ML Estimators of Variance Components
• Studies on the estimation of the slope parameter in the simple linear regression model with one-fold nested error structure
• Computable MINQUE-Type Estimates of Variance Components
• A Simple 'Synthesis'-Based Method of Variance Component Estimation
• Maximum likelihood estimation in simple linear regression with one fold nested error

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