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 -- ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.