| Package | Description |
|---|---|
| dev.nm.stat.timeseries.linear.univariate.stationaryprocess | |
| dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma |
ARMA model fitting and forecasting from an ordered observation history.
|
| Class and Description |
|---|
| InnovationsAlgorithm
The innovations algorithm is an efficient way to obtain a one step least square linear predictor
for a univariate linear time series with known auto-covariance and these properties (not limited
to ARMA processes):
\(\{x_{t}\}\) can be non-stationary.
|
| Class and Description |
|---|
| InnovationsAlgorithm
The innovations algorithm is an efficient way to obtain a one step least square linear predictor
for a univariate linear time series with known auto-covariance and these properties (not limited
to ARMA processes):
\(\{x_{t}\}\) can be non-stationary.
|
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