[R] Functions for autoregressive Regressionmodels (Mix between times series and Regression Models) ?
"Maja Schröter"
maja.schroeter at gmx.de
Tue Aug 7 14:20:46 CEST 2007
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
--
More information about the R-help
mailing list