ARIMA Models
In this chapter, we will discuss univariate time series models. These are models that only consider a single variable and create forecasts based only on the previous samples in the time series. We will start by looking at models for stationary time series data and then progress to models for non-stationary time series data. We will also discuss how to identify appropriate models based on the characteristics of time series. This will provide a powerful set of models for forecasting time series.
In this chapter, we’re going to cover the following main topics:
- Models for stationary time series
- Models for non-stationary time series
- More on model evaluation
