VCA (version 1.3.4)

getGB: Giesbrecht & Burns Approximation of the Variance-Covariance Matrix of Variance Components.

Description

Compute variance covariance matrix of variance components of a linear mixed model via the method stated in Giesbrecht and Burns (1985).

Usage

getGB(obj, tol = 1e-12)

Arguments

obj

(object) with list-type structure, e.g. VCA object fitted by ANOVA or a premature VCA object fitted by REML

tol

(numeric) values < 'tol' will be considered being equal to zero

Value

(matrix) corresponding to the Giesbrecht & Burns approximation of the variance-covariance matrix of variance components

Details

This function is not intended to be called by users and therefore not exported.

References

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

See Also

vcovVC, remlVCA, remlMM

Examples

# NOT RUN {
data(dataEP05A2_3)
fit <- anovaVCA(y~day/run, dataEP05A2_3)
fit <- solveMME(fit)		# some additional matrices required
getGB(fit)
# }