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Jun 16th, 2019
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  1. data(cars)
  2. plot(cars)
  3. lmodel <- loess(cars$dist~cars$speed,span = 0.3, degree = 1)
  4. lpred<-predict(lmodel, newdata= 5:25,se=TRUE)
  5. lines(5:25, lpred$fit,col='#000066',lwd=4)
  6. lines(5:25, lpred$fit - qt(0.975, lpred$df)*lpred$se, lty=2)
  7. lines(5:25, lpred$fit + qt(0.975, lpred$df)*lpred$se, lty=2)
  8.  
  9.  
  10. #### combination of quantreg with loess
  11.  
  12. plot(cars$speed,cars$dist)
  13. xx <- seq(min(cars$speed),max(cars$speed),1)
  14. f <- coef(rq(loess(cars$dist~cars$speed,span = 0.3, degree = 1), tau=c(0.1,0.25,0.5,0.75,0.9)) )
  15. yy <- cbind(1,xx)%*%f
  16. for(i in 1:length(taus)){
  17. lines(xx,yy[,i],col = "gray")
  18. }
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