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MSBVAR (version 0.4.0)

Markov-Switching, Bayesian, Vector Autoregression Models

Description

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.

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Version

Install

install.packages('MSBVAR')

Monthly Downloads

19

Version

0.4.0

License

GPL (>= 2)

Maintainer

Patrick Brandt

Last Published

July 21st, 2009

Functions in MSBVAR (0.4.0)

Mountain plots for summarizing forecast densities

Bivariate Granger causality testing

Printing DFEV tables

Lag decay specification check

Likelihood normalization of SVAR models

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

Compare VAR forecasts to each other or real data

Baum-Hamilton-Lindgren-Kim state-space filter

reduced.form.var

Estimation of a reduced form VAR model

Converts A0 objects to coda MCMC objects

Random draws from and density for Dirichlet distribution

Empirical CDF computations for posterior forecast samples

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

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

IsraelPalestineConflict

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

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

Gibbs sampler for coefficients of a B-SVAR model

Plots impulse responses

Utility function for generating the restriction matrix for hard condition forecasting

Gibbs-Metropolis-Hastings sampler for posterior of a Markov-switching Bayesian structural vector autoregression model

Impulse Response Function (IRF) Computation for a VAR

Plots competing sets of VAR forecasts or a single set of VAR forecasts

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

Random deviates from a Wishart distribution

Mean absolute error of VAR forecasts

Find the null space of a matrix

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

Plotting posteriors of Monte Carlo simulated impulse responses

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

Monte Carlo Integration / Simulation of Impulse Response Functions for an MSBSVAR model.

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

Subset of Data from Brandt, Colaresi, and Freeman (2007)

Generate forecasts for fitted VAR objects

Multivariate Normal Random Number Generator

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

Markov-Switching Sims-Zha Bayesian VAR Model estimation

Reduced form Sims-Zha Bayesian VAR model estimation

SZ.prior.evaluation

Sims-Zha Bayesian VAR Prior Specification Search

Structural Sims-Zha Bayesian VAR model estimation

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

var.lag.specification

Automated VAR lag specification testing

print.posterior.fit

Print method for posterior fit measures

Plots VAR forecasts and their empirical error bands

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