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Plot posterior smooths

Source: R/draw-methods.R
draw.smooth_samples.Rd

Plot posterior smooths

Usage

# S3 method for 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",
  ...
)

Arguments

object

a fitted GAM, the result of a call to mgcv::gam().

select

character, logical, or numeric; which smooths to plot. If NULL, the default, then all model smooths are drawn. Numeric select indexes the smooths in the order they are specified in the formula and stored in object. Character select matches the labels for smooths as shown for example in the output from summary(object). Logical select operates as per numeric select in the order that smooths are stored.

n_samples

numeric; if not NULL, sample n_samples from the posterior draws for plotting.

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 object.

ylab

character or expression; the label for the y axis. If not supplied, a suitable label will be generated from object.

title

character or expression; the title for the plot. See ggplot2::labs().

subtitle

character or expression; the subtitle for the plot. See ggplot2::labs().

caption

character or expression; the plot caption. See ggplot2::labs().

alpha

numeric; alpha transparency for confidence or simultaneous interval.

colour

The colour to use to draw the posterior smooths. Passed to ggplot2::geom_line() as argument colour.

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 n_contour - 1 contour lines being drawn. See ggplot2::geom_contour().

scales

character; should all univariate smooths be plotted with the same y-axis scale? If scales = "free", the default, each univariate smooth has its own y-axis scale. If scales = "fixed", a common y axis scale is used for all univariate smooths.

Currently does not affect the y-axis scale of plots of the parametric terms.

rug

logical; draw a rug plot at the bottom 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 select? If TRUE, select can only be a single string to match against.

angle

numeric; the angle at which the x axis tick labels are to be drawn passed to the angle argument of ggplot2::guide_axis().

ncol, nrow

numeric; the numbers of rows and columns over which to spread the plots

guides

character; one of "keep" (the default), "collect", or "auto". Passed to patchwork::plot_layout()

...

arguments to be passed to patchwork::wrap_plots().

Author

Gavin L. Simpson

Examples

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)


# \donttest{
## 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)

# }