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MSBVAR (version 0.6-0)

Markov-Switching, Bayesian, Vector Autoregression Models

Description

Provides methods for estimating frequentist and Bayesian Vector Autoregression (VAR) models and Markov-switching Bayesian VAR (MSBVAR). Functions for reduced form and structural VAR models are also available. Includes methods for the generating posterior inferences for these models, 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 functionality to build and evaluate models with Markov switching.

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Version

Install

install.packages('MSBVAR')

Monthly Downloads

19

Version

0.6-0

License

GPL (>= 2)

Maintainer

Patrick Brandt

Last Published

February 1st, 2011

Functions in MSBVAR (0.6-0)

Plot a parameter density summary for B-SVAR A(0) objects

Generate forecasts for fitted VAR objects

Lag decay specification check

Summary measures and plots for MS-B(S)VAR state-spaces

Likelihood normalization of SVAR models

Compare VAR forecasts to each other or real data

Impulse Response Function (IRF) Computation for a VAR

Subset of Data from Brandt, Colaresi, and Freeman (2008)

Bivariate Granger causality testing

Plots impulse responses

print.posterior.fit

Print method for posterior fit measures

Find the null space of a matrix

Printing DFEV tables

Empirical CDF computations for posterior forecast samples

IsraelPalestineConflict

Weekly Goldstein Scaled Israeli-Palestinian Conflict Data, 1979-2003

reduced.form.var

Estimation of a reduced form VAR model

Decompositions of Forecast Error Variance (DFEV) for VAR/BVAR/BSVAR models

Log density for a Wishart variate

Random draws from and density for Dirichlet distribution

Utility function for generating the restriction matrix for hard condition forecasting

Multivariate Normal Random Number Generator

Gibbs sampler for a Markov-switching Bayesian reduced form vector autoregression model

Estimates the marginal likelihood and posterior probability for VAR, BVAR, and BSVAR models

Gibbs sampler for coefficients of a B-SVAR model

var.lag.specification

Automated VAR lag specification testing

Mean absolute error of VAR forecasts

State-space filter and sampler for a Markov-switching VAR model

Plots VAR forecasts and their empirical error bands

Converts A0 objects to coda MCMC objects

Prints a list object for the VAR and BVAR models in MSBVAR

Plot function for forecasts

Summary functions for VAR / BVAR / B-SVAR model objects

Mountain plots for summarizing forecast densities

SZ.prior.evaluation

Sims-Zha Bayesian VAR Prior Specification Search

summary.forecast

Summary functions for forecasts obtained through VAR / BVAR / B-SVAR model objects

Forecast density estimation of hard condition forecasts for VAR models via MCMC

Markov-switching Bayesian reduced form vector autoregression model setup and posterior mode estimation

Gibbs sampler for posterior of Bayesian structural vector autoregression models

Monte Carlo Integration / Simulation of Impulse Response Functions

Root mean squared error of a Monte Carlo / MCMC sample of forecasts

Plotting posteriors of Monte Carlo simulated impulse responses

Forecast density estimation unconditional forecasts for VAR/BVAR/BSVAR models via MCMC

Random deviates from a Wishart distribution

Reduced form Sims-Zha Bayesian VAR model estimation

Clustering and plotting function for msbvar permuted sample output

Baum-Hamilton-Lindgren-Kim state-space filter

Structural Sims-Zha Bayesian VAR model estimation