NTS (version 1.1.3)

uTAR.est: General Estimation of TAR Models

Description

General estimation of TAR models with known threshold values. It perform LS estimation of a univariate TAR model, and can handle multiple regimes.

Usage

uTAR.est(
  y,
  arorder = c(1, 1),
  thr = c(0),
  d = 1,
  thrV = NULL,
  include.mean = c(TRUE, TRUE),
  output = TRUE
)

Value

uTAR.est returns a list with components:

data

the data matrix, y.

k

the number of regimes.

arorder

AR orders of regimes 1 and 2.

coefs

a k-by-(p+1) matrices, where k is the number of regimes. The i-th row shows the estimation results in regime i.

sigma

estimated innovational covariances for all the regimes.

thr

threshold value.

residuals

estimated innovations.

sresi

standardized residuals.

nobs

numbers of observations in different regimes.

delay

delay for threshold variable.

cnst

logical values indicating whether the constant terms are included in different regimes.

AIC

AIC value.

Arguments

y

time series.

arorder

AR order of each regime. The number of regime is the length of arorder.

thr

given threshold(s). There are k-1 threshold for a k-regime model.

d

delay for threshold variable, default is 1.

thrV

external threshold variable if any. If it is not NULL, thrV must have the same length as that of y.

include.mean

a logical value indicating whether constant terms are included. Default is TRUE.

output

a logical value for output. Default is TRUE.

Examples

phi=t(matrix(c(-0.3, 0.5,0.6,-0.3),2,2))
y=uTAR.sim(nob=200, arorder=c(2,2), phi=phi, d=2, thr=0.2, cnst=c(1,-1),sigma=c(1, 1))
thr.est=uTAR(y=y$series, p1=2, p2=2, d=2, thrQ=c(0,1),Trim=c(0.1,0.9), method="RLS")
est=uTAR.est(y=y$series, arorder=c(2,2), thr=thr.est$thr, d=2)