R Notebook

In a multiple regression model, we forecast the variable of interest using a linear combination of predictors. In an autoregression model, we forecast the variable of interest using a linear combination of past values of the variable. The term autoregression indicates that it is a regression of the variable against itself.

An autoregressive model of order \(p\) can be written as

\(y_t = c+\Phi_1 y_{t-1} + \Phi_2 y_{t-2} + ... \Phi_p y_{t-p} +\epsilon_t\)

plot(cars)