Wold's theorem, named after the Swedish mathematician Herman Wold, is a fundamental result in time series analysis. It provides a decomposition of a wide-sense stationary time series into two components: a deterministic part and a stochastic part. Specifically, Wold's theorem states that any stationary process can be represented as: 1. A sum of a deterministic component (which may include trends, seasonal effects, and other predictable elements).
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