A summary of the MCMC output can be obtained via the function TAR.summary.
TAR.summary returns the posterior mean, median, standard deviation and
the lower and upper bound of the 95% Bayes posterior interval for all parameters,
all botained from the sampling period only, after burn-in.
TAR.summary(x, lagp1, lagp2, constant = 1)A matrix of the MCMC output of estimater parameters.
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).
The vector of non-zero autoregressive lags for the upper regime. (regime two)
Use the CONSTANT option to fit a model with/without a constant term (1/0). By default CONSTANT=1.