We now explore various methods for forecasting (i.e. predicting) the next value(s) in a time series. A time series is a sequence of observations y1, …, yn. We usually think of the subscripts as representing evenly spaced time intervals (seconds, minutes, months, seasons, years, etc.).
- Basic forecasting methods:
- Stochastic Process
- Autoregressive Processes
- Moving Average Processes
- Autoregressive Moving Average Processes (ARMA)
- Autoregressive Integrated Moving Average Processes (ARIMA)