Time Series Seasonal Decomposition
Using Seasonal Decomposition to Inform the SARIMA Model Selection of Soybean Prices in Python.
There are a variety of approaches you can use when working with time series data, such as linear models, ARIMA models, exponential smoothing methods, and recurrent neural networks (RNNs). In this post, I will focus on an extension of the ARIMA model that also accounts for seasonality in the data: the SARIMA model.
