TAR.lik: Log-likelihood function

In BAYSTAR: On Bayesian Analysis of Threshold Autoregressive Models

Log-likelihood function

Description

To calculate the model log-likelihood function.

Usage

TAR.lik(ay, p1, p2, ph.1, ph.2, sig.1, sig.2, 
        lagd, thres, lagp1, lagp2, constant = 1, thresVar)

Arguments

A list containing:

ay	The real data set. (input)
p1	Number of AR coefficients in regime one.
p2	Number of AR coefficients 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 of AR model in the regime one.
sig.2	The error terms of AR model in the 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)
constant	Use the CONSTANT option to fit a model with/without a constant term (1/0). By default CONSTANT=1.
thresVar	Exogenous threshold variable. (if missing, the series x is used)

Author(s)

Cathy W.S. Chen, F.C. Liu

BAYSTAR documentation built on May 15, 2022, 1:06 a.m.