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MSBVAR (version 0.7-0)

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

0.7-0

License

GPL (>= 2)

Maintainer

Patrick Brandt

Last Published

July 23rd, 2012

Functions in MSBVAR (0.7-0)

IsraelPalestineConflict

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

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

Printing DFEV tables

Plot function for forecasts

Find the null space of a matrix

Mean absolute error of VAR forecasts

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

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

Quarterly U.S. GDP Growth, 1952Q3-1984Q4

Gibbs sampler for coefficients of a B-SVAR model

Lag decay specification check

Random draws from and density for Dirichlet distribution

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

Utility function for generating the restriction matrix for hard condition forecasting

Simulate a Markov-switching VAR (MSVAR) process

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

Plots impulse responses

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

Random deviates from a Wishart distribution

var.lag.specification

Automated VAR lag specification testing

Likelihood normalization of SVAR models

Impulse Response Function (IRF) Computation for a VAR

Simulate (univariate) Markov-switching autoregressive (MSAR) data

Compare VAR forecasts to each other or real data

Multivariate Normal Random Number Generator

Markov-switching vector autoregression (MSVAR) estimator

Plots VAR forecasts and their empirical error bands

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

Bivariate Granger causality testing

Generate forecasts for fitted VAR objects

Reduced form Sims-Zha Bayesian VAR model estimation

Clustering and plotting function for msbvar permuted sample output

Structural Sims-Zha Bayesian VAR model estimation

Monte Carlo Integration / Simulation of Impulse Response Functions

initialize.msbvar

Initializes the mode-finder for a Markov-switching Bayesian VAR model

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

Gibbs sampler for posterior of Bayesian structural vector autoregression models

Estimates the marginal likelihood or log posterior probability for BVAR, BSVAR, and MSBVAR models

Converts A0 objects to coda MCMC objects

Plotting posteriors of Monte Carlo simulated impulse responses

print.posterior.fit

Print method for posterior fit measures

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

reduced.form.var

Estimation of a reduced form VAR model

Empirical CDF computations for posterior forecast samples

Log density for a Wishart variate

summary.forecast

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

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

SZ.prior.evaluation

Sims-Zha Bayesian VAR Prior Specification Search

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

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

Mountain plots for summarizing forecast densities