r - Plot quantiles of distribution in ggplot2 with facets -

i'm plotting number of different distributions of first differences number of regression models in ggplot. facilitate interpretation of differences, want mark 2.5% , 97.5% percentile of each distribution. since doing quite few plots, , because data grouped in 2 dimension (model , type), define , plot respective percentiles in ggplot environment. plotting distributions using facets gets me want except percentiles. of course more manually, ideally want find solution still able use facet_grid, since spared me lot of hassle trying fit different plots together.

here's example using simulated data:

df.example <- data.frame(model = rep(c("a", "b"), length.out = 500),                        type = rep(c("t1", "t2", "t2", "t1"),                        length.outh = 250), value = rnorm(1000))   ggplot(df.example, aes(x = value)) +  facet_grid(type ~ model) +  geom_density(aes(fill = model, colour = model)) 

i've tried add quantiles in 2 ways. first 1 produces error message:

 ggplot(df.example, aes(x = value)) +  facet_grid(. ~ model) +  geom_density(aes(fill = model, colour = model)) +  geom_vline(aes(x = value), xintercept = quantile(value, probs = c(.025, .975))) 

error in quantile(value, probs = c(0.025, 0.975)) : object 'value' not found 

while second 1 gets me quantiles the complete variable , not sub-densities. is, plotted quantiles identical 4 densities.

 ggplot(df.example, aes(x = value)) +  facet_grid(type ~ model) +  geom_density(aes(fill = model, colour = model)) +  geom_vline(xintercept = quantile(df.example$value, probs = c(.025, .975))) 

i consequently wonder if there way plot specific quantiles each subgroup within ggplot2 environment?

greatly appreciate input.

you can calculate quantiles beforehand.

using example data:

library (dplyr) d2 <- df.example %>%   group_by(model, type) %>%   summarize(lower = quantile(value, probs = .025),             upper = quantile(value, probs = .975)) 

and plot this:

ggplot(df.example, aes(x = value)) +   facet_grid(type ~ model) +   geom_density(aes(fill = model, colour = model)) +   geom_vline(data = d2, aes(xintercept = lower)) +   geom_vline(data = d2, aes(xintercept = upper))