MSBVAR (version 0.4.0)

BHLK.filter: Baum-Hamilton-Lindgren-Kim state-space filter

Description

Implements a Baum-Hamilton-Lindgren-Kim state-space filter for a multivariate Markov-switching model.

Usage

BHLK.filter(u, Sigma, Q)

Value

x$T \times h$ matrix of the filtered regime probabilities.

Details

Estimates the Markov-switching regime probabilities for an MSBVAR model. Conditional on the BVAR(p) model, the residuals are used to filter the data. The estimation is done using compiled C++ code for speed.

References

Sims, Christopher A. and Daniel F. Waggoner and Tao Zha. 2008. "Methods for inference in large multiple-equation Markov-switching models" Journal of Econometrics 146(2):255--274.

Kim, C.J. and C.R. Nelson. 1999. State-space models with regime switching. Cambridge, Mass: MIT Press. Krolzig, Hans-Martin. 1997. Markov-Switching Vector Autoregressions: Modeling, Statistical Inference, and Application to Business Cycle Analysis.

See Also

msbvar

Examples

# Sets up and estimates a set of filter probabilities
h <- 2
m <- 2
TT <- 100
u <- array(rnorm(TT*m*h), c(TT, m, h))
Sigma <- array(diag(m), c(m, m, h))
Q <- matrix(c(0.99, 0.2, 0.01, 0.8), h, h)
x <- BHLK.filter(u, Sigma, Q)