Compute variance covariance matrix of variance components of a linear mixed model via the method stated in Giesbrecht and Burns (1985).
getGB(obj, tol = 1e-12)
(object) with list-type structure, e.g. VCA
object fitted by ANOVA
or a premature VCA
object fitted by REML
(numeric) values < 'tol' will be considered being equal to zero
(matrix) corresponding to the Giesbrecht & Burns approximation of the variance-covariance matrix of variance components
This function is not intended to be called by users and therefore not exported.
Searle, S.R, Casella, G., McCulloch, C.E. (1992), Variance Components, Wiley New York
Giesbrecht, F.G. and Burns, J.C. (1985), Two-Stage Analysis Based on a Mixed Model: Large-Sample Asymptotic Theory and Small-Sample Simulation Results, Biometrics 41, p. 477-486
# NOT RUN {
data(dataEP05A2_3)
fit <- anovaVCA(y~day/run, dataEP05A2_3)
fit <- solveMME(fit) # some additional matrices required
getGB(fit)
# }
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