Plotting sequence of slices of 2D smooth effect

This function allows to slice a multi-dimensional (D > 2) smooth effect, and to plot the resulting sequence of 2D slices in an array of plots.

plotSlice(x, fix, a.facet = list(), ...)

Arguments

x	a smooth effect object, extracted using mgcViz::sm.
fix	a named list of vectors, where the i-th entry of each vector indicates the value we want to use for the covariate for i-th slice. When plotting a smooth in (d+2) dimensions, we need d vectors, because d variables must be fixed. All vectors must have either the same length (the number of slices) or length 1. fix can contain at most 2 vectors, so if d>=5, we need to set at least one covariate to a scalar.
a.facet	arguments to be passed to ggplot2::facet_wrap or ggplot2::facet_grid. The former gets called when fix contains one vector, the latter when fix contains two vectors.
...	further arguments to be passed to plot.mgcv.smooth.MD.

Value

An objects of class plotSmooth.

Examples

### Example 1: plotting slices of 3D smooth
# Simulate data and fit GAM
library(mgcViz)
n <- 1e3
x <- rnorm(n); y <- rnorm(n); z <- rnorm(n)
ob <- (x-z)^2 + (y-z)^2 + rnorm(n)
b <- gam(ob ~ s(x, y, z))
v <- getViz(b)

# Get plot of slices and add layers
pl <- plotSlice(x = sm(v, 1),
                fix = list("z" = seq(-2, 2, length.out = 9)))
pl + l_fitRaster() + l_fitContour() + l_points() + l_rug()

# Over-ride default layout
pl <- plotSlice(x = sm(v, 1),
                fix = list("z" = seq(-2, 2, length.out = 9)),
                a.facet = list(nrow = 2))
pl + l_fitRaster() + l_fitContour() + theme(panel.spacing = unit(0.5, "lines"))

### Example 2: plotting slices of 4D smooth
# Simulate data and fit GAM
n <- 5e3
x <- rnorm(n); y <- rnorm(n); z <- rnorm(n); z2 <- rnorm(n)
ob <- (x-z)^2 + (y-z)^2 + z2^3 + rnorm(n)
b <- bam(ob ~ s(x, y, z, z2), discrete = TRUE)
v <- getViz(b)

# Plot slices across "z" and "x"
pl <- plotSlice(x = sm(v, 1),
                fix = list("z" = seq(-2, 2, length.out = 3), "x" = c(-1, 0, 1)))
pl + l_fitRaster() + l_fitContour() + l_points() + l_rug()

# Plot slices across "x", keeping "z" fixed
pl <- plotSlice(x = sm(v, 1),
                fix = list("z" = 0, "x" = seq(-3, 3, length.out = 9)))
pl + l_fitRaster() + l_fitContour() + l_points() + l_rug()