Giesbrecht & Burns Approximation of the Variance-Covariance Matrix of Variance Components
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)
obj |
(object) with list-type structure, e.g. |
tol |
(numeric) values < 'tol' will be considered being equal to zero |
This function is not intended to be called by users and therefore not exported.
(matrix) corresponding to the Giesbrecht & Burns approximation of the variance-covariance matrix of variance components
Andre Schuetzenmeister andre.schuetzenmeister@roche.com, Florian Dufey florian.dufey@contractors.roche.com
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) ## End(Not run)
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