plotConvergence: Plot convergence time series for parameter vectors from an...

In joineRML: Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes

Plot convergence time series for parameter vectors from an mjoint object

Description

Plot convergence time series for parameter vectors from an mjoint object.

Usage

plotConvergence(object, params = "gamma", discard = FALSE)

Arguments

object	an object inheriting from class mjoint for a joint model of time-to-event and multivariate longitudinal data.
params	a string indicating what parameters are to be shown. Options are params='gamma' for the time-to-event sub-model covariate coefficients, including the latent association parameters; params='beta' for the longitudinal sub-model fixed effects coefficients; params='sigma2' for the residual error variances from the longitudinal sub-model; params='D' for the lower triangular matrix of the variance-covariance matrix of random effects; params='loglik' for the log-likelihood.
discard	logical; if TRUE then the 'burn-in' phase iterations of the MCEM algorithm are discarded. Default is discard=FALSE.

Author(s)

Graeme L. Hickey ([e-mail])

References

Wei GC, Tanner MA. A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms. J Am Stat Assoc. 1990; 85(411): 699-704.

See Also

plot.mjoint, plot.default, par, abline.

joineRML documentation built on Jan. 22, 2023, 1:18 a.m.