mTAR.sim: Generate Two-Regime (TAR) Models

In NTS: Nonlinear Time Series Analysis

Generate Two-Regime (TAR) Models

Description

Generates multivariate two-regime threshold autoregressive models.

Usage

mTAR.sim(
  nob,
  thr,
  phi1,
  phi2,
  sigma1,
  sigma2 = NULL,
  c1 = NULL,
  c2 = NULL,
  delay = c(1, 1),
  ini = 500
)

Arguments

nob	number of observations.
thr	threshold value.
phi1	VAR coefficient matrix of regime 1.
phi2	VAR coefficient matrix of regime 2.
sigma1	innovational covariance matrix of regime 1.
sigma2	innovational covariance matrix of regime 2.
c1	constant vector of regime 1.
c2	constant vector of regime 2.
delay	two elements (i,d) with "i" being the component index and "d" the delay for threshold variable.
ini	burn-in period.

Value

mTAR.sim returns a list with following components:

series	a time series following the multivariate two-regime VAR model.
at	innovation of the time series.
threshold	threshold value.
delay	two elements (i,d) with "i" being the component index and "d" the delay for threshold variable.
n1	number of observations in regime 1.
n2	number of observations in regime 2.

Examples

phi1=matrix(c(0.5,0.7,0.3,0.2),2,2)
phi2=matrix(c(0.4,0.6,0.5,-0.5),2,2)
sigma1=matrix(c(1,0,0,1),2,2)
sigma2=matrix(c(1,0,0,1),2,2)
c1=c(0,0)
c2=c(0,0)
delay=c(1,1)
y=mTAR.sim(100,0,phi1,phi2,sigma1,sigma2,c1,c2,delay,ini=500)

NTS documentation built on Sept. 25, 2023, 1:08 a.m.