Set different bandwidths in ggplot2 facet_grid plotting - r

Question

Suppose I have a data set called "data", and is generated through:
library(reshape2) # Reshape data, needed in command "melt"
library(ggplot2) # apply ggplot
density <-rep (0.05, each=800)
tau <-rep (0.05, each=800)
# define two different models: network and non-network
model <-rep(1:2, each=400, times=1)
## Create data and factors for the plot
df <- melt(rnorm(800, -3, 0.5))
data <- as.data.frame(cbind(density, tau, model, df$value))
data$density <- factor(data$density,levels=0.05,
labels=c("Density=0.05"))
data$tau <- factor(data$tau,levels=0.05,
labels=c("tau=0.05"))
data$model<- factor(data$model,levels=c(1,2),
labels=c("Yes",
"No"))
ggplot(data=data, aes(x=V4, shape=model, colour=model, lty=model)) +
stat_density(adjust=1, geom="line",position="identity") +
facet_grid(tau~density, scale="free") +
geom_vline(xintercept=-3, lty="dashed") +
ggtitle("Kernel Density") +
xlab("Data") +
ylab("Kernel Density") +
theme(plot.title=element_text(face="bold", size=17), # change fond size of title
axis.text.x= element_text(size=14),
axis.text.y= element_text(size=14),
legend.title=element_text(size=14),
legend.text =element_text(size=12),
strip.text.x=element_text(size=14), # change fond size of x_axis
strip.text.y=element_text(size=14)) # change fond size of y_axis
Looking at the data, variable V4 is separated into two subsets by the model (Yes [1:400] and No [401:800]), and the kernel density is plotted without change the original bandwidth since adjust=1.
What I want to do is: for the Yes model, the bandwidth changes to 10 times of the original, but for the No model, the bandwidth keeps unchanged. Can I do something like letting the adjust=c(10, 1)? I know how to realize this by plot()+lines(), but I want to do this in ggplot() for further analysis.

Answer 1

I wouldn't recommend this, since it creates a very misleading plot, but you can do it with two calls to stat_density(...).
ggplot(data=data, aes(x=V4, shape=model, colour=model, lty=model)) +
stat_density(data=data[data$model=="Yes",], adjust=10,
geom="line",position="identity") +
stat_density(data=data[data$model=="No",], adjust=1,
geom="line",position="identity") +
facet_grid(tau~density, scale="free") +
geom_vline(xintercept=-3, lty="dashed") +
ggtitle("Kernel Density") +
xlab("Data") +
ylab("Kernel Density") +
theme(plot.title=element_text(face="bold", size=17),
axis.text.x= element_text(size=14),
axis.text.y= element_text(size=14),
legend.title=element_text(size=14),
legend.text =element_text(size=12),
strip.text.x=element_text(size=14),
strip.text.y=element_text(size=14))