varjmcm (version 0.1.1)

covjmcm_hpc: Calculate the estimation of the covariance of estimated parameters in a HPC model, via the explicit formula.

Description

covjmcm_hpc gives the estimation of the covariance of estimated parameters in a HPC model using the explicit formula, which is the inverse of the estimated Fisher's information matrix.

Usage

covjmcm_hpc(object)

Arguments

object

a fitted joint mean-covariance model of class "jmcmMod", returned by the function jmcm.

Value

an estimated covariance matrix of the estimated parameters in a HPC model.

References

[1] W. Zhang, C. Leng, and C. Y. Tang(2015), "A joint modelling approach for longitudinal studies," Journal of the Royal Statistical Society. Series B. 77, 219-238.

See Also

covjmcm, covjmcm_mcd, and covjmcm_acd

Examples

# NOT RUN {
##This may take more than 1 min.
# }
# NOT RUN {
cattleA <- cattle[cattle$group=='A', ]
fit.hpc <- jmcm(weight|id|I(ceiling(day/14+1))~1|1,
               data = cattleA, cov.method = "hpc",
               triple = c(8,3,4))
cov.hpc <- covjmcm_hpc(fit.hpc)
# }