Wold decomposition
Theorem taught in Dependence along a series, part of Time series
Wold decomposition
| Type | Theorem |
| Taught in | Dependence along a series |
| Part | Time series |
If \{X_t\} is weakly stationary with mean zero, then X_t=\sum_{j=0}^{\infty} a_j\varepsilon_{t-j}+\nu_t, where the \varepsilon_t are uncorrelated with mean zero and variance \sigma^2, the coefficients a_j are constants, \nu_t is linearly determined by its own past, and the innovations are uncorrelated with \nu_t. If the mean is \mu, add \mu to the right-hand side.
Used in
- Taught in Dependence along a series, where the derivation and examples are.
- Also used in Forecasting
- All 7 questions on Dependence along a series