ComputePostmeanHnew {bkmr} | R Documentation |
h
at a new predictor valuesCompute the posterior mean and variance of h
at a new predictor values
ComputePostmeanHnew(fit, y = NULL, Z = NULL, X = NULL, Znew = NULL, sel = NULL, method = "approx")
fit |
An object containing the results returned by a the |
y |
a vector of outcome data of length |
Z |
an |
X |
an |
Znew |
matrix of new predictor values at which to predict new |
sel |
selects which iterations of the MCMC sampler to use for inference; see details |
method |
method for obtaining posterior summaries at a vector of new points. Options are "approx" and "exact"; defaults to "approx", which is faster particularly for large datasets; see details |
If method == "approx"
then calls the function ComputePostmeanHnew.approx
. In this case, the argument sel
defaults to the second half of the MCMC iterations.
If method == "exact"
then calls the function ComputePostmeanHnew.exact
. In this case, the argument sel
defaults to keeping every 10 iterations after dropping the first 50% of samples, or if this results in fewer than 100 iterations, than 100 iterations are kept
For guided examples and additional information, go to https://jenfb.github.io/bkmr/overview.html