# predictPlot
# command to make a prediction interval plot for a simple linear regression
# x is the explanatory variable
# y is the response variable
# interval="prediction" is a confidence interval for individual observations.
# interval="confidence" is a confidence interval for the population mean.

# -------------- Directions ------------------------------------
# Save this file as a text file on your computer.
# From R, use the File menu and select "Import R Source Code..."
# Browse for the file predictPlot.R that you saved earlier.
# You can then use predictPlot as a function.
#
# ------------- Example ----------------------------------------
# ex0723 <- read.table(file.choose(),header=T,sep=",")
# attach(ex0723)
# predictPlot(DURATION,INTERVAL)
# predictPlot(DURATION,INTERVAL,interval="prediction")
# predictPlot(DURATION,INTERVAL,interval="prediction",level=0.99)

predictPlot <- function(x,y,interval=c("confidence","prediction"),level=0.95) {
  interval <- match.arg(interval)
  fit <- lm(y ~ x)
  r <- range(x)
  new <- data.frame(x=seq(r[1],r[2],length=200))
  limits <- predict.lm(fit,new,interval=interval,level=level)
  ylim <- range(c(y,limits[,2],limits[,3]))
  matplot(new$x,limits[,-1],xlab=deparse(substitute(x)),ylab=deparse(substitute(y)),lty=2,col=2,type="l",xlim=r,ylim=ylim)
  points(x,y)
  abline(fit)
  invisible()
}