Posterior Predictions of Smooth Terms — posterior

Compute posterior predictions of smooth s and t2 terms of models fitted with brms.

# S3 method for brmsfit
posterior_smooths(
  object,
  smooth,
  newdata = NULL,
  resp = NULL,
  dpar = NULL,
  nlpar = NULL,
  ndraws = NULL,
  draw_ids = NULL,
  ...
)

posterior_smooths(object, ...)

Arguments

object: An object of class brmsfit.
smooth: Name of a single smooth term for which predictions should be computed.
newdata: An optional data.frame for which to evaluate predictions. If NULL (default), the original data of the model is used. Only those variables appearing in the chosen smooth term are required.
resp: Optional names of response variables. If specified, predictions are performed only for the specified response variables.
dpar: Optional name of a predicted distributional parameter. If specified, expected predictions of this parameters are returned.
nlpar: Optional name of a predicted non-linear parameter. If specified, expected predictions of this parameters are returned.
ndraws: Positive integer indicating how many posterior draws should be used. If NULL (the default) all draws are used. Ignored if draw_ids is not NULL.
draw_ids: An integer vector specifying the posterior draws to be used. If NULL (the default), all draws are used.
...: Currently ignored.

Value

An S x N matrix, where S is the number of posterior draws and N is the number of observations.

Examples

if (FALSE) {
set.seed(0)
dat <- mgcv::gamSim(1, n = 200, scale = 2)
fit <- brm(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat)
summary(fit)

newdata <- data.frame(x2 = seq(0, 1, 10))
str(posterior_smooths(fit, smooth = "s(x2)", newdata = newdata))
}