TAR.simu {BAYSTAR} | R Documentation |
Simulated data from TAR model
Description
To generate the simulated data from TAR(2;p1,p2) model.
Usage
TAR.simu(nob, p1, p2, ph.1, ph.2, sig.1, sig.2, lagd, thres, lagp1, lagp2)
Arguments
nob |
Number of observations that we want to simulate. |
p1 |
Number of AR coefficient in regime one. |
p2 |
Number of AR coefficient in regime two. |
ph.1 |
The vector of AR parameters in regime one. |
ph.2 |
The vector of AR parameters in regime two. |
sig.1 |
The error terms in regime one. |
sig.2 |
The error terms in regime two. |
lagd |
The delay lag parameter. |
thres |
The threshold parameter. |
lagp1 |
The vector of non-zero autoregressive lags for the lower regime. (regime one); e.g. An AR model with p1=3, it could be non-zero lags 1,3, and 5 would set lagp1<-c(1,3,5). |
lagp2 |
The vector of non-zero autoregressive lags for the upper regime. (regime two) |
Author(s)
Cathy W.S. Chen, Edward Lin
Examples
## Set the true values of all parameters
nob<- 2000 ## No. of observations
lagd<- 1 ## delay lag of threshold variable
r<- 0.4 ## r is the threshold value
sig.1<- 0.8; sig.2<- 0.5 ## variances of error distributions for two regimes
p1<- 2; p2<- 2 ## No. of covariate in two regimes
ph.1<- c(0.1,-0.4,0.3) ## mean coefficients for regime 1
ph.2<- c(0.2,0.3,0.3) ## mean coefficients for regime 2
lagp1<-1:2
lagp2<-1:2
yt<- TAR.simu(nob,p1,p2,ph.1,ph.2,sig.1,sig.2,lagd,r,lagp1,lagp2)
[Package BAYSTAR version 0.2-10 Index]