This repository should serve as a compendium of various Bayesian time series models. It consists of estimation procedures and various functions for analysing time series data efficiently. This toolbox does not claim to be complete and will be expanded by demand of its users.
The latest development version can be installed from GitHub.
devtools::install_github("mboeck11/BTSM")Note that Mac OS needs gfortran binary packages to be installed. See also: https://gcc.gnu.org/wiki/GFortranBinaries. Please make sure that you have installed all package dependencies, this can cause troubles.
This package focuses on multivariate time series models estimated in a Bayesian fashion. The table below summarises available estimation function for different models and which tool functions are available for each model.
| Model | Estimation | IRFs | Predictions | FEVD | HD |
|---|---|---|---|---|---|
| Bayesian Vector Autoregression | bvar() |
yes | yes | yes | yes |
| Bayesian Vector Error Correction Model | bvec() |
yes | no | no | no |
| Bayesian Interacted Vector Autoregression | bivar() |
yes | no | no | no |
| Bayesian Panel Vector Autoregressions | bpvar() |
no | no | no | no |
| Bayesian Interacted Panel Vector Autoregression | no | no | no | no | no |
| Time-varying Parameter Bayesian Vector Autoregression | tvpbvar() |
yes | yes | no | no |
We also provide S3methods for each function as summarized in the next table
| Model | Function | print() |
summary() |
logLik() |
coef() |
vcov() |
resid() |
|---|---|---|---|---|---|---|---|
| Bayesian Vector Autoregression | bvar() |
yes | yes | yes | no | no | no |
| Bayesian Vector Error Correction Model | bvec() |
no | no | no | no | no | no |
| Bayesian Interacted Vector Autoregression | bivar() |
no | no | no | no | no | no |
| Bayesian Panel Vector Autoregressions | bpvar() |
no | no | no | no | no | no |
| Bayesian Interacted Panel Vector Autoregression | no | no | no | no | no | no | no |
| Time-varying Parameter Bayesian Vector Autoregression | tvpbvar() |
yes | no | no | no | no | no |
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