[R] How to use R to estimate a model which has two sets of lagged time series independent variables

[Gabor Grothendieck]

If you don't need a complex error structure then the dyn package
(and also the dynlm package) can do it. Using R's builtin
EuStockMarkets time series:

library(dyn)

z <- as.zoo(EuStockMarkets)
mod1 <- dyn$lm(DAX ~ lag(DAX, -(1:2)) + lag(FTSE, -(0:2)), z)
mod1

# compare to model without FTSE
mod2 <- dyn$lm(DAX ~ lag(DAX, -(1:2)), z)
anova(mod2, mod1)

On Dec 13, 2007 8:59 AM, Suen, Michael <Michael.Suen at inginvestment.com> wrote:
> Hi,
>
> I would like to use R to estimate the following model:
>
> X(t) = a + b1*X(t-1) + b2*X(t-2) + c1*Y(t) + c2*Y(t-1) + c3*Y(t-2)
>
> Is there any R function that performs this type of estimation? I know
> that if I only have one time series (i.e. lagged value of X) on the
> right hand side then there are R functions to do the estimation. I am
> thinking a work around by preparing X(t-1), X(t-2),Y(t),Y(t-1) and
> Y(t-2) as five independent variables and use the lm() function to
> performance the estimation. Please advise. Thanks.
>
> Michael
>
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