pred.mvt {GJRM} | R Documentation |
Function to predict mean and variance of marginal distributions, as well as Kendall's tau
Description
It takes a fitted gjrm
object produced
by gjrm()
and
produces predictions and respective intervals.
Usage
pred.mvt(x, eq, fun = "mean", n.sim = 100, prob.lev = 0.05, smooth.no = NULL, ...)
Arguments
x |
A fitted |
eq |
The equation number. |
fun |
Either mean, variance or tau. |
n.sim |
The number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used to calculate intervals. It may be increased if more precision is required. |
prob.lev |
Probability of the left and right tails of the posterior distribution used for interval calculations. |
smooth.no |
Smooth number if the interest is in a particular smooth and not the additive predictor(s). |
... |
Other parameters. |
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
See Also
[Package GJRM version 0.2-6.5 Index]