Function marg.mv can be used to calculate marginal means/variances, with corresponding interval obtained using posterior simulation.
marg.mv(x, eq, newdata, fun = "mean", n.sim = 100, prob.lev = 0.05, bin.model = NULL)
It returns three values: lower confidence interval limit, estimated marginal mean or variance and upper interval limit.
Probability level used.
It returns a vector containing simulated values of the marginal mean or variance. This is used to calculate intervals.
A fitted marg.mv object as produced by the respective fitting function.
Number of equation of interest.
A data frame with one row, which must be provided.
Either mean or variance.
Number of simulated coefficient vectors from the posterior distribution of the estimated model parameters.
Overall probability of the left and right tails of the simulated distribution used for interval calculations.
If a two part or hurdle model is used then this is the object of a binary regression model fitted using gam() from mgcv.
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
marg.mv() calculates the marginal mean or variance. Posterior simulation is used to obtain a confidence/credible interval.
GJRM-package, gjrm