Other packages > Find by keyword >

BGVAR  

Bayesian Global Vector Autoregressions
View on CRAN: Click here


Download and install BGVAR package within the R console
Install from CRAN:
install.packages("BGVAR")

Install from Github:
library("remotes")
install_github("cran/BGVAR")

Install by package version:
library("remotes")
install_version("BGVAR", "2.5.9")



Attach the package and use:
library("BGVAR")
Maintained by
Maximilian Boeck
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-19
Latest Update: 2024-09-30
Description:
Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 . Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available. The package has a companion paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, Vol. 104(9), pp. 1-28 .
How to cite:
Maximilian Boeck (2020). BGVAR: Bayesian Global Vector Autoregressions. R package version 2.5.9, https://cran.r-project.org/web/packages/BGVAR. Accessed 05 Aug. 2026.
Previous versions and publish date:
2.0.0 (2020-06-19 13:10), 2.0.1 (2020-06-24 14:10), 2.1.0 (2020-09-07 14:50), 2.1.1 (2020-09-07 23:50), 2.1.2 (2020-09-14 23:40), 2.1.3 (2020-09-30 20:20), 2.1.4 (2020-11-14 15:50), 2.1.5 (2020-11-15 18:10), 2.2.0 (2021-05-03 11:10), 2.2.3 (2021-07-17 12:10), 2.2.4 (2021-07-20 09:20), 2.3.0 (2021-08-10 12:20), 2.3.1 (2021-09-10 11:10), 2.4.0 (2021-10-06 11:00), 2.4.1 (2021-11-04 09:10), 2.4.2 (2021-11-04 15:30), 2.4.3 (2021-11-06 16:00), 2.4.4 (2022-04-01 12:40), 2.4.5 (2022-04-04 12:50), 2.4.6 (2022-04-12 09:22), 2.5.0 (2022-05-02 11:40), 2.5.1 (2022-09-03 01:00), 2.5.2 (2022-10-26 17:27), 2.5.3 (2023-12-09 00:40), 2.5.4 (2023-12-11 09:00), 2.5.5 (2023-12-13 23:30), 2.5.6 (2024-07-03 19:20), 2.5.7 (2024-07-07 16:50), 2.5.8 (2024-09-30 16:50), (2026-07-09 07:57)
Other packages that cited BGVAR R package
View BGVAR citation profile
Other R packages that BGVAR depends, imports, suggests or enhances
Complete documentation for BGVAR
Functions, R codes and Examples using the BGVAR R package
Some associated functions: BGVAR-package . add_shockinfo . avg.pair.cc . bgvar . coef . conv.diag . dic . eerData . excel_to_list . fevd . fitted . get_shockinfo . gfevd . hd . irf . list_to_matrix . logLik . lps . matrix_to_list . monthlyData . pesaranData . plot . predict . resid.corr.test . residuals . rmse . summary . testdata . vcov . 
Some associated R codes: BGVAR.R . RcppExports.R . bgvar-package.R . fevd.R . hd.R . helpers.R . irf.R . plot.R . predict.R . utils.R . zzz.R .  Full BGVAR package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

dhReg  
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency  
noisyr  
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency  
kernelPSI  
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency  
dcov  
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA