trendovou
Trendovou is a term used in data science to describe a family of methods, tools, and concepts focused on identifying, modeling, and forecasting long-term trends in time-series data. The core idea is to separate a series into a trend component, seasonal and cyclic components, and residual noise, enabling clearer interpretation and more accurate forecasting.
The name is commonly linked to Central European data-analytics discourse, reflecting linguistic roots in the Czech
Typical features include trend extraction through smoothing or regression-based methods, decomposition into trend, seasonal, and residual
Implementations vary in licensing and scope. Some trendovou tooling is open-source and Python-based, with APIs for
Limitations include sensitivity to non-stationarity, structural breaks, and regime shifts; choice of decomposition method can influence