I'm trying to augment a plot with contours from a 2D Gaussian distribution with known mean and covariance. Ideally I would just have to specify the function and it would be plotted in 2D (like stat_function except for 2 dimensions). I can do it with geom_raster by generating a grid of probabilites. Can I use geom_contour2d somehow instead?
m <- c(.5, -.5)
sigma <- matrix(c(1,.5,.5,1), nrow=2)
data.grid <- expand.grid(s.1 = seq(-3, 3, length.out=200), s.2 = seq(-3, 3, length.out=200))
q.samp <- cbind(data.grid, prob = mvtnorm::dmvnorm(data.grid, mean = m, sigma = sigma))
ggplot(q.samp, aes(x=s.1, y=s.2)) +
geom_raster(aes(fill = prob)) +
coord_fixed(xlim = c(-3, 3), ylim = c(-3, 3), ratio = 1)
