R help - Jul 2004 - dynamic regression

Greetings:
 
Is there an simple way to do dynamic regressions in R? 
>From what I've seen, one must use arima() and construct the X matrix
with lagged values etc. and modify Y as well.
 
Thanks,
 
Bob

		
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Dear Bob,

If you mean regression with autocorrelated errors, take a look at the gls
(generalised least squares) function in the nlme package.

I hope this helps,
 John 
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of bob mccall
> Sent: Friday, July 30, 2004 10:13 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] dynamic regression
> 
> Greetings:
>  
> Is there an simple way to do dynamic regressions in R? 
> >From what I've seen, one must use arima() and construct the 
> X matrix with lagged values etc. and modify Y as well.
>  
> Thanks,
>  
> Bob

On Fri, 30 Jul 2004 08:13:05 -0700 (PDT) bob mccall wrote:
> Greetings:
>  
> Is there an simple way to do dynamic regressions in R? 
> >From what I've seen, one must use arima() and construct the X
matrix
> >with lagged values etc. and modify Y as well.
If you want OLS regression with lagged regressors you could also
transform your data using lag() and window() and then use lm().
E.g. for a multiplicative SARIMA(1,0,0)(1,0,0) model for the seatbelt
data you could do something like:

data(UKDriverDeaths)
seatbelt <- log10(UKDriverDeaths)
seatbelt <- cbind(seatbelt, lag(seatbelt, k = -1), 
  lag(seatbelt, k = -12))
colnames(seatbelt) <- c("y", "ylag1", "ylag12")
seatbelt <- window(seatbelt, start = c(1970, 1), end = c(1984, 12))

lm(y ~ ylag1 + ylag12, data = seatbelt)

hth,
Z

> Thanks,
>  
> Bob
> 
> 		
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> 
> 
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