mTAR.est | R Documentation |
Estimation of multivariate TAR models with given thresholds. It can handle multiple regimes.
mTAR.est(
y,
arorder = c(1, 1),
thr = c(0),
delay = c(1, 1),
thrV = NULL,
include.mean = c(TRUE, TRUE),
output = TRUE
)
y |
vector time series. |
arorder |
AR order of each regime. The number of regime is length of arorder. |
thr |
threshold value(s). There are k-1 threshold for a k-regime model. |
delay |
two elements (i,d) with "i" being the component and "d" the delay for threshold variable. |
thrV |
external threshold variable if any. If thrV is not null, it must have the same number of observations as y-series. |
include.mean |
logical values indicating whether constant terms are included. Default is TRUE for all. |
output |
a logical value indicating four output. Default is TRUE. |
mTAR.est returns a list with the following components:
data |
the data matrix, |
k |
the dimension of |
arorder |
AR orders of regimes 1 and 2. |
beta |
a ( |
sigma |
estimated innovational covariance matrices of regimes 1 and 2. |
thr |
threshold value. |
residuals |
estimated innovations. |
sresi |
standardized residuals. |
nobs |
numbers of observations in different regimes. |
cnst |
logical values indicating whether the constant terms are included in different regimes. |
AIC |
AIC value. |
delay |
two elements ( |
thrV |
values of threshold variable. |
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)
est=mTAR.est(y$series,c(1,1),0,delay)
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