Bayesian Vector Autoregression Models, Impulse Responses and Forecasting.
Provides methods for estimating frequentist and
Bayesian Vector Autoregression (VAR) models.  Also includes
methods for the generating posterior inferences for VAR
forecasts, impulse responses (using likelihood-based error bands),
and forecast error decompositions.  Also includes utility functions
for plotting forecasts and impulse responses, and generating draws
from Wishart and singular multivariate normal densities.  Future
versions will include Bayesian Structural VAR (B-SVAR) models and
possibly some models with Markov switching.

Provides methods for estimating frequentist and
Bayesian Vector Autoregression (VAR) models.  Functions for reduced
form and structural VAR models are also available. Includes
methods for the generating posterior inferences for VAR
forecasts, impulse responses (using likelihood-based error bands),
and forecast error decompositions.  Also includes utility functions
for plotting forecasts and impulse responses, and generating draws
from Wishart and singular multivariate normal densities.  Future
versions will include some models with Markov switching.

R (>= 2.4.0), KernSmooth, xtable, coda, methods

Markov-Switching Bayesian Vector Autoregression Models
Patrick T. Brandt <pbrandt@utdallas.edu>, Justin Appleby <appleby@utdallas.edu>

Markov-Switching, Bayesian, Vector Autoregression Models
R (>= 2.8.0), KernSmooth, xtable, coda, bit, mvtnorm
Provides methods for estimating frequentist and Bayesian
Vector Autoregression (VAR) models.  Functions for reduced form
and structural VAR models are also available. Includes methods
for the generating posterior inferences for VAR forecasts,
impulse responses (using likelihood-based error bands), and
forecast error decompositions.  Also includes utility functions
for plotting forecasts and impulse responses, and generating
draws from Wishart and singular multivariate normal densities.
Current version includes some limited functionality to build
models with Markov switching.