What is Seasonal Decomposition of Time Series (STL)?
Seasonal Decomposition of Time Series (STL) is a technique that breaks down a time series into three main components: trend, seasonality, and residuals. This method helps in understanding and isolating the underlying patterns in epidemiological data. STL is particularly useful because it can handle both additive and multiplicative seasonal effects, making it versatile for different types of epidemiological data.
