How to get the confidence intervals for LOWESS fit using R?
I didn't find any satisfactory answer to the confidence intervals (CIs) for LOWESS regression line of the 'stats' package of R:
plot(cars, main = "lowess(cars)")
lines(lowess(cars), col = 2)
But I'm unsure how to draw a 95% CI around it?? However, I know I could get the estimated variance from
V = s^2*sum(w^2)
where, s2= estimated error variance, and w=weights applied to the X. Therefore, the 95% CIs should be
Y plus/minus 2*sqrt(V(Y))
I know there's a way of getting the CIs from loess fit, but I'd rather prefer LOWESS because it is robust. Thanks for your suggestions.
Answer
You can do this with predict() and loess(). lowess is older than loess and has fewer features, though it is a bit faster. But in this context, I'd use loess as follows.
plot(cars)
plx<-predict(loess(cars$dist ~ cars$speed), se=T)
lines(cars$speed,plx$fit)
lines(cars$speed,plx$fit - qt(0.975,plx$df)*plx$se, lty=2)
lines(cars$speed,plx$fit + qt(0.975,plx$df)*plx$se, lty=2)
