How do I add the curve from GauPro in ggplot? - r

Question

GauPro is an R library for fitting gaussian processes. You can also get it to produce a nuce predicted curve for you.
The documentation for GauPro uses builtin r plotting functions to do plots like this:
gp <- GauPro(x,y) ## fit a gaussian process model to x & y
plot(x,y) ## plots the x,y points
curve(gp$predict(x), add=T, col=2) ## adds the predicted curve from the gaussian process
What would be the equivalent using ggplot? I can get the points to show up, but I can't quite figure out how to add the curve.
GauPro documentation I refer to is here

Answer 1

We can do this by building a little data frame of predictions. Let's start by loading the necessary packages and creating some sample data:
library(GauPro)
library(ggplot2)
set.seed(69)
x <- 1:10
y <- cumsum(runif(10))
Now we can create our model and plot it using the same plotting functions shown in the vignette you linked:
gp <- GauPro(x, y)
plot(x, y)
curve(gp$predict(x), add = TRUE, col = 2)
Now if we want to customize this plot using ggplot, we need a data frame with columns for the x values at which we wish to predict, the y prediction at that point, and a column each for upper and lower 95% confidence intervals. We can obtain the x values like this:
new_x <- seq(min(x), max(x), length.out = 100)
and we can get the three sets of corresponding y values using predict like this:
predict_df <- predict(gp, new_x, se.fit = TRUE)
predict_df$x <- new_x
predict_df$y <- predict_df$mean
predict_df$lower <- predict_df$y - 1.96 * predict_df$se
predict_df$upper <- predict_df$y + 1.96 * predict_df$se
this is now quite straightforward to plot in ggplot with themes customized as you choose:
ggplot(data.frame(x, y), aes(x, y)) +
geom_point() +
geom_line(data = predict_df, color = "deepskyblue4", linetype = 2) +
geom_ribbon(data = predict_df, aes(ymin = lower, ymax = upper),
alpha = 0.2, fill = "deepskyblue4") +
theme_minimal()
Created on 2020-07-29 by the reprex package (v0.3.0)