I want to plot a data set where the size of the points are proportional to the x-variable and have a regression line with a 95% prediction interval. The "sample" code I have written is as follows:
  # Create random data and run regression
  x <- rnorm(40)
  y <- 0.5 * x + rnorm(40)
  plot.dta <- data.frame(y, x)
  mod <- lm(y ~ x, data = plot.dta)
  # Create values for prediction interval
  x.new <- data.frame(x = seq(-2.5, 2.5, length = 1000))
  pred <- predict(mod,, newdata = x.new, interval = "prediction")
  pred <- data.frame(cbind(x.new, pred))
  # plot the data w/ regression line and prediction interval
  p <- ggplot(pred, aes(x = x, y = upr)) + 
    geom_line(aes(y = lwr), color = "#666666", linetype = "dashed") +
    geom_line(aes(y = upr), color = "#666666", linetype = "dashed") +
    geom_line(aes(y = fit)) + 
    geom_point(data = plot.dta, aes(y = y, size = x))
  p
This produces the following plot:

Obviously, the legend is not too helpful here. I would like to have one entry in the legend for the points, say, labeled "data", one grey, dashed line labeled "95% PI" and one entry with a black line labeled "Regression line."
 
     
    