public class MultivariateForecastOneStep extends Object
| Constructor and Description |
|---|
MultivariateForecastOneStep(MultivariateIntTimeTimeSeries Xt,
MultivariateAutoCovarianceFunction K)
Construct an instance of InnovationAlgorithm for a multivariate time series with known auto-covariance structure.
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| Modifier and Type | Method and Description |
|---|---|
ImmutableMatrix |
covariance(int n)
Get the covariance matrix for prediction errors for \(\hat{x}_{n+1}\), made at time n.
|
ImmutableMatrix |
theta(int i,
int j)
Get the coefficients of the linear predictor.
|
ImmutableVector |
xHat(int n)
Get the one-step prediction \(\hat{X}_{n+1} = P_{\mathfrak{S_n}}X_{n+1}\), made at time n.
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public MultivariateForecastOneStep(MultivariateIntTimeTimeSeries Xt, MultivariateAutoCovarianceFunction K)
Xt - an m-dimensional time series, length tK - auto-covariance function K(i, j) = E(Xi * Xj'), a m x m matrixpublic ImmutableVector xHat(int n)
n - time, ranging from 0 to T, the end of observation timepublic ImmutableMatrix theta(int i, int j)
i - i, ranging from 1 to tj - j, ranging from 1 to tpublic ImmutableMatrix covariance(int n)
n - time, ranging from 0 to T, the end of observation timeCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.