View source: R/conditional_smooths.R
conditional_smooths.brmsfit | R Documentation |
Display smooth s
and t2
terms of models
fitted with brms.
## S3 method for class 'brmsfit'
conditional_smooths(
x,
smooths = NULL,
int_conditions = NULL,
prob = 0.95,
spaghetti = FALSE,
resolution = 100,
too_far = 0,
ndraws = NULL,
draw_ids = NULL,
nsamples = NULL,
subset = NULL,
probs = NULL,
...
)
conditional_smooths(x, ...)
x |
An object of class |
smooths |
Optional character vector of smooth terms
to display. If |
int_conditions |
An optional named |
prob |
A value between 0 and 1 indicating the desired probability to be covered by the uncertainty intervals. The default is 0.95. |
spaghetti |
Logical. Indicates if predictions should
be visualized via spaghetti plots. Only applied for numeric
predictors. If |
resolution |
Number of support points used to generate
the plots. Higher resolution leads to smoother plots.
Defaults to |
too_far |
Positive number.
For surface plots only: Grid points that are too
far away from the actual data points can be excluded from the plot.
|
ndraws |
Positive integer indicating how many
posterior draws should be used.
If |
draw_ids |
An integer vector specifying
the posterior draws to be used.
If |
nsamples |
Deprecated alias of |
subset |
Deprecated alias of |
probs |
(Deprecated) The quantiles to be used in the computation of
uncertainty intervals. Please use argument |
... |
Currently ignored. |
Two-dimensional smooth terms will be visualized using either contour or raster plots.
For the brmsfit
method,
an object of class brms_conditional_effects
. See
conditional_effects
for
more details and documentation of the related plotting function.
## Not run:
set.seed(0)
dat <- mgcv::gamSim(1, n = 200, scale = 2)
fit <- brm(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat)
# show all smooth terms
plot(conditional_smooths(fit), rug = TRUE, ask = FALSE)
# show only the smooth term s(x2)
plot(conditional_smooths(fit, smooths = "s(x2)"), ask = FALSE)
# fit and plot a two-dimensional smooth term
fit2 <- brm(y ~ t2(x0, x2), data = dat)
ms <- conditional_smooths(fit2)
plot(ms, stype = "contour")
plot(ms, stype = "raster")
## End(Not run)
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