TAR.summary

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&lt;-c(1,3,5).

lagp1

The vector of non-zero autoregressive lags for the upper regime. (regime two)

lagp2

Use the CONSTANT option to fit a model with/without a constant term (1/0). By default CONSTANT=1.

constant

A summary of the MCMC output can be obtained via the function <code>TAR.summary</code>.
  <code>TAR.summary</code> 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.

methods

The manuscript introduces the BAYSTAR package, which
        provides the functionality for Bayesian estimation in
        autoregressive threshold models.

TAR.summary: Calculate summary statistics for all parameters

Description

Usage

Arguments