Maximum Likelihood Estimation of Variance Components in Repeated Measures Designs Assuming Autoregressive Errors

DOI10.2307/2530665zbMath0613.62096OpenAlexW2317490057MaRDI QIDQ4720599

Erik V. Nordheim, Hussein Mansour, J. J. Rutledge

Publication date: 1985

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/2530665

zbMATH Keywords

Monte Carlo resultsMaximum likelihoodcorrelated errorsLinear modelsautoregressive errorsestimation of variance componentsfirst-order nonstationary autoregressive process

Mathematics Subject Classification ID

Analysis of variance and covariance (ANOVA) (62J10)

Related Items (5)

Repeated measurements, log likelihood ratio tests and small samples ⋮ Panel regression models for measuring multidimensional poverty dynamics ⋮ Repeated measurements designs - a review ⋮ Optimal incomplete block designs for general dependence structures ⋮ Book review of: B. T. West et al., Linear mixed models. A practical guide using statistical software

This page was built for publication: Maximum Likelihood Estimation of Variance Components in Repeated Measures Designs Assuming Autoregressive Errors