conditional_smooths.brmsfit {brms}  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, subset = NULL, nsamples = 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.

subset 
A numeric vector specifying
the posterior samples to be used.
If 
nsamples 
Positive integer indicating how many
posterior samples should be used.
If 
probs 
(Deprecated) The quantiles to be used in the computation of
uncertainty intervals. Please use argument 
... 
Currently ignored. 
Twodimensional 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 twodimensional 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)