draw.smooth_samples | R Documentation |
Plot posterior smooths
## S3 method for class 'smooth_samples' draw( object, select = NULL, n_samples = NULL, seed = NULL, xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, alpha = 1, colour = "black", contour = FALSE, contour_col = "black", n_contour = NULL, scales = c("free", "fixed"), rug = TRUE, partial_match = FALSE, angle = NULL, ncol = NULL, nrow = NULL, guides = "keep", ... )
object |
a fitted GAM, the result of a call to |
select |
character, logical, or numeric; which smooths to plot. If
|
n_samples |
numeric; if not |
seed |
numeric; random seed to be used to if sampling draws. |
xlab |
character or expression; the label for the x axis. If not
supplied, a suitable label will be generated from |
ylab |
character or expression; the label for the y axis. If not
supplied, a suitable label will be generated from |
title |
character or expression; the title for the plot. See
|
subtitle |
character or expression; the subtitle for the plot. See
|
caption |
character or expression; the plot caption. See
|
alpha |
numeric; alpha transparency for confidence or simultaneous interval. |
colour |
The colour to use to draw the posterior smooths. Passed to
|
contour |
logical; should contour lines be added to smooth surfaces? |
contour_col |
colour specification for contour lines. |
n_contour |
numeric; the number of contour bins. Will result in
|
scales |
character; should all univariate smooths be plotted with the
same y-axis scale? If Currently does not affect the y-axis scale of plots of the parametric terms. |
rug |
logical; draw a rug plot at the botom of each plot for 1-D smooths or plot locations of data for higher dimensions. |
partial_match |
logical; should smooths be selected by partial matches
with |
angle |
numeric; the angle at which the x axis tick labels are to be
drawn passed to the |
ncol, nrow |
numeric; the numbers of rows and columns over which to spread the plots |
guides |
character; one of |
... |
arguments to be passed to |
Gavin L. Simpson
load_mgcv() dat1 <- data_sim("eg1", n = 400, dist = "normal", scale = 1, seed = 1) ## a single smooth GAM m1 <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat1, method = "REML") ## posterior smooths from m1 sm1 <- smooth_samples(m1, n = 15, seed = 23478) ## plot draw(sm1, alpha = 0.7) ## plot only 5 randomly smapled draws draw(sm1, n_samples = 5, alpha = 0.7) ## A factor-by smooth example dat2 <- data_sim("eg4", n = 400, dist = "normal", scale = 1, seed = 1) ## a multi-smooth GAM with a factor-by smooth m2 <- gam(y ~ fac + s(x2, by = fac) + s(x0), data = dat2, method = "REML") ## posterior smooths from m1 sm2 <- smooth_samples(m2, n = 15, seed = 23478) ## plot, this time selecting only the factor-by smooth draw(sm2, select = "s(x2)", partial_match = TRUE, alpha = 0.7) ## A 2D smooth example dat3 <- data_sim("eg2", n = 400, dist = "normal", scale = 1, seed = 1) ## fit a 2D smooth m3 <- gam(y ~ te(x, z), data = dat3, method = "REML") ## get samples sm3 <- smooth_samples(m3, n = 10) ## plot just 6 of the draws, with contour line overlays draw(sm3, n_samples = 6, contour = TRUE, seed = 42)
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