Try this:
lm(a.ts ~ factor(cycle(a.ts)) - 1)
On Thu, Mar 18, 2010 at 12:30 PM, Len Vir <lenvir at gmail.com>
wrote:> # Dear List,
>
> # I want to characterize a time series according to its Quarter components.
>
> # My data ("a.ts":
> http://docs.google.com/View?id=dfvvwzr2_478cr9k4cdb)? look like:
>
> #???????????????? Qtr1????????? Qtr2????????? Qtr3????????? Qtr4
> #?? 1948 -0.0714961837? 0.0101747827? 0.0654816569 -0.0227830729
> #?? 1949 -0.1175517556? 0.1151378692? 0.1015777858 -0.1971535900
> #?? 1950? 0.0716002123? 0.2551020416? 0.0977574743 -0.0739337411
> #??? ...
>
>
> #? The time series is 216 long
>
> #? The easiest way I could figure out, is to create
> #? Quarter dummies:
>
> Q1 <- rep(c(1,0,0,0),54)
> Q2 <- rep(c(0,1,0,0),54)
> Q3 <- rep(c(0,0,1,0),54)
> Q4 <- rep(c(0,0,0,1),54)
>
> qtr <- cbind(Q1,Q2,Q3,Q4)
>
> # and then regress my data on the dummies.
>
> summary(lm(a.ts ~ qtr - 1))
>
> # The regression on 'Quarters' works fine.
> # It does exactly what I want it to do.
>
> # But!? Surely there must be a more elegant way
> #?????? to accomplish the same thing ?!
>
> # I have looked at the following packages (amongst others):
> # tseries, timeSeries, TSA, AER, fSeries, vars, FinTS, xts, fArma,
> # fRegression, tsfa, uroot, urca, ...
>
> # without finding anything more convenient (simpler, nicer!).
>
> # Any suggestion?
>
> # Thank you.
>
> # Len Vir
>
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