Adding a weighted least squares trendline in ggplot2

Question

I am preparing a plot using ggplot2, and I want to add a trendline that is based on a weighted least squares estimation.

In base graphics this can be done by sending a WLS model to abline:

mod0 <- lm(ds$dMNP~ds$MNP)
mod1 <- lm(ds$dMNP~ds$MNP, weights = ds$Asset)

symbols(ds$dMNP~ds$MNP, circles=ds$r, inches=0.35)
#abline(mod0)
abline(mod1)

in ggplot2 I set the argument weight in geom_smooth but nothing changes:

ggplot(ds, aes(x=MNP, y=dMNP, size=Asset) + 
  geom_point(shape=21) +
  geom_smooth(method = "lm", weight="Asset", color="black", show.legend = FALSE)

this gives me the same plot as

ggplot(ds, aes(x=MNP, y=dMNP, size=Asset) + 
  geom_point(shape=21) +
  geom_smooth(method = "lm", color="black", show.legend = FALSE)

Answer 1

I'm late, but for posterity and clarity, here is the full solution:

ggplot(ds, aes(x = MNP, y = dMNP, size = Asset)) + 
  geom_point(shape = 21) +
  geom_smooth(method = "lm", mapping = aes(weight = Asset), 
              color = "black", show.legend = FALSE)

Don't put the weight name in quotes.