bvartools v0.0.1

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Bayesian Inference of Vector Autoregressive Models

Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Koop and Korobilis (2010) <doi:10.1561/0800000013> and Luetkepohl (2007, ISBN: 9783540262398).

Functions in bvartools

Name Description
bvartools bvartools: Bayesian Inference of Vector Autoregressive Models
plot.bvarprd Plotting Forecasts of BVAR Models
post_coint_kls_sur Posterior Draw for Cointegration Models
post_coint_kls Posterior Draw for Cointegration Models
ssvs Stochastic Search Variable Selection
post_normal_sur Posterior Draw from a Normal Distribution
thin Thinning Posterior Draws
post_normal Posterior Draw from a Normal Distribution
kalman_dk Durbin and Koopman Simulation Smoother
irf Impulse Response Function
bvar Bayesian Vector Autoregression Objects
bvec_to_bvar Transform a VECM to VAR in levels
fevd Forecast Error Variance Decomposition
bvs Bayesian Variable Selection
gen_var Vector Autoregressive Model Input
e6 German interest and inflation rate data
e1 West German economic time series data
bvec Bayesian Vector Error Correction Objects
gen_vec Vector Error Correction Model Input
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Vignettes of bvartools

Name
bsvar.Rmd
bvartools.Rmd
bvec.Rmd
ssvs.Rmd
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Last month downloads

Details

Date 2019-06-09
License GPL (>= 2)
LinkingTo Rcpp, RcppArmadillo
Encoding UTF-8
RoxygenNote 6.1.1
URL https://github.com/franzmohr/bvartools
BugReports https://github.com/franzmohr/bvartools/issues
VignetteBuilder knitr
NeedsCompilation yes
Packaged 2019-06-09 08:44:14 UTC; franz
Repository CRAN
Date/Publication 2019-06-11 10:10:19 UTC

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