Time series decomposition over open weather data from Luxembourg

Time series decomposition is a powerful statistical method that decomposes a signal into several components (usually a trend, a periodic and a random component). These components can be used to do forecasting, prediction or extrapolation of missing data. This topic is relatively old, since the main research paper in the field dates back to 1990. In R language, one of the most famous function for time series decomposition is the stl function. Read More…