Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- unm <- read.csv("enrollment.csv")
- plot(unm$unem,unm$enroll,xlab="Unemployment (%)",ylab="Enrollment")
- #
- # We could use our commands, but there is built in tools
- #
- res <- lm(enroll~unem,data=unm)
- names(res)
- res$coef
- res$fitted
- res$resid
- summary(res)
- #
- # We will discuss some of this output more in detail on Monday
- #
- plot(unm$unem,unm$enroll,xlab="Unemployment (%)",ylab="Enrollment")
- abline(res)
- confint(res)
- confint(res,level=.90)
- #
- # Predicted values based on model
- #
- xh <- data.frame(unem=7)
- predict(res,newdata=xh)
- xh <- data.frame(unem=c(6,7,8,9,10))
- predict(res,newdata=xh)
- predict(res,newdata=xh,se.fit=T)
- predict(res,newdata=xh,interval="confidence",level=.95)
- predict(res,newdata=xh,interval="prediction",level=.95)
- #
- # Can we graph this in a useful fashion?
- #
- attach(unm) # Break apart the file so we have easy access to data
- plot(unem,enroll,xlab="Unemployment (%)",ylab="Enrollment",pch=20)
- abline(res,lwd=2)
- newData <- data.frame(unem=seq(min(unem),max(unem),by=(max(unem)-min(unem))/45))
- conf.lim <- predict(res,newData,interval="confidence")
- pred.lim <- predict(res,newData,interval="prediction")
- matlines(newData$unem,conf.lim[,-1],col="red",lty=2)
- matlines(newData$unem,pred.lim[,-1],col="green",lty=3)
- legend(8.5,7000,legend=c("Fitted Line","Confidence Bands","Prediction Bands"),
- lty=c(1,2,3),col=c("black","red","green"))
Add Comment
Please, Sign In to add comment