public class CointegrationMLE extends Object
| Constructor and Description |
|---|
CointegrationMLE(MultivariateSimpleTimeSeries ts,
boolean intercept)
Perform the Johansen MLE procedure on a multivariate time series,
using the EIGEN test, with the number of lags = 2.
|
CointegrationMLE(MultivariateSimpleTimeSeries ts,
boolean intercept,
int p)
Perform the Johansen MLE procedure on a multivariate time series, using
the EIGEN test.
|
CointegrationMLE(MultivariateSimpleTimeSeries ts,
boolean intercept,
int p,
Matrix D)
Perform the Johansen MLE procedure on a multivariate time series.
|
| Modifier and Type | Method and Description |
|---|---|
Matrix |
alpha()
Get the set of adjusting coefficients, by columns.
|
Matrix |
beta()
Get the set of cointegrating factors, by columns.
|
Vector |
beta(int r)
Get the r-th cointegrating factor, counting from 1.
|
Vector |
getEigenvalues()
Get the set of real eigenvalues.
|
int |
n()
Get the number of rows of the multivariate time series used in
regression.
|
int |
rank()
Get the rank of the system, i.e., the number of (real) eigenvalues.
|
public CointegrationMLE(MultivariateSimpleTimeSeries ts, boolean intercept, int p, Matrix D)
ts - a multivariate time seriesintercept - indicate whether an intercept is included in the
estimationp - the number of lags, e.g., 2D - the exogenous factor matrix (excluding the intercept)public CointegrationMLE(MultivariateSimpleTimeSeries ts, boolean intercept, int p)
ts - a multivariate time seriesintercept - indicate whether an intercept is included in the
estimationp - the number of lags, e.g., 2public CointegrationMLE(MultivariateSimpleTimeSeries ts, boolean intercept)
ts - a multivariate time seriesintercept - indicate whether an intercept is included in the
estimationpublic Matrix alpha()
public Matrix beta()
public Vector beta(int r)
r - an indexpublic Vector getEigenvalues()
public int rank()
public int n()
ts.size - pCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.