Conformal prediction
Conformal predicions using locally weighted conformal inference with a split-conformal algorithm
confpred(object, data, newdata = data, alpha = 0.05, mad, ...)
object
: Model object (lm, glm or similar with predict method) or formula (lm)data
: data.framenewdata
: New data.frame to make predictions foralpha
: Level of prediction intervalmad
: Conditional model (formula) for the MAD (locally-weighted CP)...
: Additional arguments to lower level functionsdata.frame with fitted (fit), lower (lwr) and upper (upr) predictions bands.
set.seed(123) n <- 200 x <- seq(0,6,length.out=n) delta <- 3 ss <- exp(-1+1.5*cos((x-delta))) ee <- rnorm(n,sd=ss) y <- (x-delta)+3*cos(x+4.5-delta)+ee d <- data.frame(y=y,x=x) newd <- data.frame(x=seq(0,6,length.out=50)) cc <- confpred(lm(y~splines::ns(x,knots=c(1,3,5)),data=d), data=d, newdata=newd) if (interactive()) { plot(y~x,pch=16,col=lava::Col("black"),ylim=c(-10,10),xlab="X",ylab="Y") with(cc, lava::confband(newd$x,lwr,upr,fit, lwd=3,polygon=TRUE,col=Col("blue"),border=FALSE)) }