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.
|
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.
|
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.