Integration
Explore the concept of integration in time series analysis to transform non-stationary data into stationary data by differencing observations. Understand how integrating once or twice impacts data trends and how combining integration with models like AR enhances forecasting accuracy. This lesson equips you to apply integration techniques effectively in Python-based time series forecasting.
We'll cover the following...
We'll cover the following...
Understanding integration
In the context of time series data, integrating means taking the difference of observations so the data can become stationary. In practice, we replace each value with the difference between the current value and ...