gam plots with ggplot

Question

I need to create some gam plots in ggplot. I can do them with the general plot function, but am unsure how to do with ggplot. Here is my code and plots with the regular plot function. I'm using the College data set from the ISLR package.

train.2 <- sample(dim(College)[1],2*dim(College)[1]/3)
train.college <- College[train.2,]
test.college <- College[-train.2,]
gam.college <- gam(Outstate~Private+s(Room.Board)+s(Personal)+s(PhD)+s(perc.alumni)+s(Expend)+s(Grad.Rate), data=train.college)
par(mfrow=c(2,2))
plot(gam.college, se=TRUE,col="blue")

Answer 1

See update below old answer.

Old answer:

There is an implementation of GAM plotting using ggplot2 in voxel library. Here is how you would go about it:

library(ISLR)
library(mgcv)
library(voxel)
library(tidyverse)
library(gridExtra)
data(College)

set.seed(1)
train.2 <- sample(dim(College)[1],2*dim(College)[1]/3)
train.college <- College[train.2,]
test.college <- College[-train.2,]
gam.college <- gam(Outstate~Private+s(Room.Board)+s(Personal)+s(PhD)+s(perc.alumni)+s(Expend)+s(Grad.Rate), data=train.college)

vars <- c("Room.Board", "Personal", "PhD", "perc.alumni","Expend", "Grad.Rate")

map(vars, function(x){
  p <- plotGAM(gam.college, smooth.cov = x) #plot customization goes here
  g <- ggplotGrob(p)
}) %>%
  {grid.arrange(grobs = (.), ncol = 2, nrow = 3)}

after a bunch of errors: In plotGAM(gam.college, smooth.cov = x) : There are one or more factors in the model fit, please consider plotting by group since plot might be unprecise

To compare to the plot.gam:

par(mfrow=c(2,3))
plot(gam.college, se=TRUE,col="blue")

You might also want to plot the observed values:

map(vars, function(x){
  p <- plotGAM(gam.college, smooth.cov = x) +
    geom_point(data = train.college, aes_string(y = "Outstate", x = x ), alpha = 0.2) +
    geom_rug(data = train.college, aes_string(y = "Outstate", x = x ), alpha = 0.2)
  g <- ggplotGrob(p)
}) %>%
  {grid.arrange(grobs = (.), ncol = 3, nrow = 2)}

or per group (especially important if you used the by argument (interaction in gam).

map(vars, function(x){
  p <- plotGAM(gam.college, smooth.cov = x, groupCovs = "Private") +
    geom_point(data = train.college, aes_string(y = "Outstate", x = x, color= "Private"), alpha = 0.2) +
    geom_rug(data = train.college, aes_string(y = "Outstate", x = x, color= "Private"  ), alpha = 0.2) +
    scale_color_manual("Private", values = c("#868686FF", "#0073C2FF")) +
    theme(legend.position="none")
  g <- ggplotGrob(p)
}) %>%
  {grid.arrange(grobs = (.), ncol = 3, nrow = 2)}

Update, 08. Jan. 2020.

I currently think the package mgcViz offers superior functionality compared to the voxel::plotGAMfunction. An example using the above data set and models:

library(mgcViz)
viz <- getViz(gam.college)
print(plot(viz, allTerms = T), pages = 1)

plot customization is similar go ggplot2 syntax:

trt <- plot(viz, allTerms = T) +
  l_points() +
  l_fitLine(linetype = 1)  +
  l_ciLine(linetype = 3) +
  l_ciBar() +
  l_rug() +
  theme_grey() 

print(trt, pages = 1)

This vignette shows many more examples.