[R] Functions for autoregressive Regressionmodels (Mix between times series and Regression Models) ?

["Maja Schröter"]

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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