Guide to Autoregressive Models
AR(p) Model
The AR(p) model extends the AR(1) model by considering multiple lagged variables. It captures more complex dependencies in the data, making it suitable for scenarios where the previous values have a significant influence on the current value.
ARIMA Model
The ARIMA (Autoregressive Integrated Moving Average) model combines autoregressive, differencing, and moving average components. It is a powerful modeling technique capable of handling both trended and stationary time series data.
