[R] Functions for autoregressive Regressionmodels (Mix between times series and Regression Models) ?
Gabor Grothendieck
ggrothendieck at gmail.com
Tue Aug 7 14:42:50 CEST 2007
arima (see ?arima) supports explanatory variables in the xreg= argument.
On 8/7/07, "Maja Schröter" <maja.schroeter at gmx.de> wrote:
> Hello everybody,
>
> I've a question about "autoregressive Regressionmodels".
>
> Let Y[1],.....,Y[n], be a time series.
>
> Given the model:
>
> Y[t] = phi[1]*Y[t-1] + phi[2]*Y[t-1] + ... + phi[p]*Y[t-p] + x_t^T*beta + u_t,
>
>
> where x_t=(x[1t],x[2t],....x[mt]) and beta=(beta[1],...,beta[m]) and u_t~(0,1)
>
> I want to estimate the coefficients phi and beta.
>
> Are in R any functions or packages for "autoregressive Regressionmodel" with special summaries?. I'm not meaning the function "ar".
>
>
> Example: I have the data
>
> working.time <- rnorm(100) # Y
> vacation <- rnorm(100) #x1
> bank.holidays <- rnorm(100) #x2
> illnes <- rnorm(100) #x3
> education <- rnorm(100) #x3
>
>
>
> Now I want to analyse:
>
> Y[t] = phi[1]*Y[t-1] + phi[2]*Y[t-1] + ... + phi[p]Y[t-p] + beta1*vacation_t +beta2*bank.holidays + beta3*illnes + beta4*eductation + u_t-
>
>
>
> Has anyone an idea?
>
> I would be more than glad if so.
>
> Thank you VERY much in advance.
>
> Kindly regards from the Eastern Part of Berlin,
>
> Maja
>
> --
>
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