R help - Feb 2012 - Fitting polynomial (power greater than 2)

Hey all, first time poster here. I'm new to R and working on my first real
programming and forecasting asignment. I'm using unemployment data from
1948-2012.  I successfully completed part a and the linear fit for part b,
but i am really struggling fitting a polynomial with a power greater than 2
to my forecast. I'll upload my R code at the bottom. Any help is very much
appreciated! Thank You!

(a) Produce a time-series plot of your data.
 (b) Fit linear, polynomial (use a power greater than 2), and R?s best fit
models to your series.

rm(list=ls(all=TRUE))
z=read.table("longtermunempdata.txt")
names(z)= c("Unemployment")
attach(z)
TIME=seq(1,769,by=1)

Unemployment_ts<-ts(Unemployment,start=1948,freq=12)
#quartz()
#plot(stl(Unemployment_ts,s.window="periodic"))

#1A
quartz()
plot(TIME, Unemployment, xlab="Year", ylab="Long Term
Unemployment",type='l')

#1B Linear
quartz()
plot(TIME,Unemployment,type="l", xlab="Year",ylab="Long
Term Unemployment")
modelu=lm(Unemployment~TIME)
summary(modelu)
abline(modelu,col="red3")

modelu=lm(Unemployment~TIME)
#1B Linear vs TS
quartz()
par(mfrow=c(2,1))
plot(TIME, Unemployment, xlab="Year", ylab="Long Term
Unemployment",type='l')
abline(modelu,col="red3",lwd=2)
plot(TIME,modelu$res,xlab="Year",ylab="Long Term
Unemployment",type='l')

--
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Sent from the R help mailing list archive at Nabble.com.

This looks like homework, which is generally discouraged here.  You
should at the least admit that it is homework and tell what resources
your teacher has OK'd you to use.

Since you did show what you have done so far and are not just asking
for a handout, here is a hint:

?poly

On Tue, Feb 7, 2012 at 9:34 PM, dkendall44 <dkendall44 at gmail.com>
wrote:
> Hey all, first time poster here. I'm new to R and working on my first
real
> programming and forecasting asignment. I'm using unemployment data from
> 1948-2012. ?I successfully completed part a and the linear fit for part b,
> but i am really struggling fitting a polynomial with a power greater than 2
> to my forecast. I'll upload my R code at the bottom. Any help is very
much
> appreciated! Thank You!
>
> (a) Produce a time-series plot of your data.
> ?(b) Fit linear, polynomial (use a power greater than 2), and R?s best fit
> models to your series.
>
> rm(list=ls(all=TRUE))
> z=read.table("longtermunempdata.txt")
> names(z)= c("Unemployment")
> attach(z)
> TIME=seq(1,769,by=1)
>
> Unemployment_ts<-ts(Unemployment,start=1948,freq=12)
> #quartz()
> #plot(stl(Unemployment_ts,s.window="periodic"))
>
> #1A
> quartz()
> plot(TIME, Unemployment, xlab="Year", ylab="Long Term
> Unemployment",type='l')
>
> #1B Linear
> quartz()
> plot(TIME,Unemployment,type="l",
xlab="Year",ylab="Long Term Unemployment")
> modelu=lm(Unemployment~TIME)
> summary(modelu)
> abline(modelu,col="red3")
>
> modelu=lm(Unemployment~TIME)
> #1B Linear vs TS
> quartz()
> par(mfrow=c(2,1))
> plot(TIME, Unemployment, xlab="Year", ylab="Long Term
> Unemployment",type='l')
> abline(modelu,col="red3",lwd=2)
> plot(TIME,modelu$res,xlab="Year",ylab="Long Term
Unemployment",type='l')
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/Fitting-polynomial-power-greater-than-2-tp4368026p4368026.html
> Sent from the R help mailing list archive at Nabble.com.
>
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> and provide commented, minimal, self-contained, reproducible code.


-- 
Gregory (Greg) L. Snow Ph.D.
538280 at gmail.com