# mTAR.est: Estimation of Multivariate TAR Models In NTS: Nonlinear Time Series Analysis

## Description

Estimation of multivariate TAR models with given thresholds. It can handle multiple regimes.

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```mTAR.est( y, arorder = c(1, 1), thr = c(0), delay = c(1, 1), thrV = NULL, include.mean = c(TRUE, TRUE), output = TRUE ) ```

## Arguments

 `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.

## Value

mTAR.est returns a list with the following components:

 `data` the data matrix, `y`. `k` the dimension of `y`. `arorder` AR orders of regimes 1 and 2. `beta` a (`p*k+1`)-by-(`2k`) matrices. The first `k` columns show the estimation results in regime 1, and the second `k` columns show these in regime 2. `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 (`i,d`) with "`i`" being the component and "`d`" the delay for threshold variable. `thrV` values of threshold variable.

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```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) ```

NTS documentation built on Aug. 6, 2020, 5:08 p.m.