Introduction | Workflow | Producing candidate models | Draw posteriors | Forecasting | Evaluation | In-sample plots | Out-of-sample plots | Pooling forecasts | Adding forecasts from other sources | Citing bvartools | References

Data | Set up models | Priors | Initial values | Posterior simulation | Model selection | Citing bvartools | Literature

Introduction | Data | Model set-up | Priors | Initial values and posterior draws | Evaluation | Summary statistics for a period | Coefficient paths | Volatility paths | Impulse responses for a period | Forecasts | Other combinations | Citing bvartools | References

Introduction | Data | Model set-up | Priors | Initial values and posterior draws | Evaluation | Summary statistics for a period | Coefficient and volatility paths | A prior centred on the maximum likelihood estimate | Impulse responses and forecasts | Citing bvartools | References

When to use the estimator | A simple time series model | Reading the output | Confidence intervals and predictions | Robust standard errors | A panel model | One coefficient per panel | Panel-corrected standard errors | Gaps in the time variable | Models estimated with plm | Tidy output | References

Introduction | Data | Priors | Adding initial values | Estimation | User-specific algorithm | Default algorithm | A prior centred on the maximum likelihood estimate | Evaluation | Forecasts | Forecast error impulse response | Forecast error variance decomposition | Citing bvartools | References

Introduction | Model set-up | Data | Setting up a model | Adding prior hyperparameters | Adding initial values | Obtaining posterior draws | Evaluation | Summary statistics | Does it estimate the quantile it was asked for? | The scale of the asymmetric Laplace | A grid of quantiles | Time varying parameters | What these models do not do | Citing bvartools | References

Introduction | Model set-up | Data | Setting up a model | Adding prior hyperparameters | Adding initial values | Obtaining posterior draws | Evaluation | Inspect posterior draws | Summary statistics | Thin results | Application | Forecasts | Impulse response analysis | Forecast error impulse response | Orthogonalised impulse response | Generalised impulse response | Variance decomposition | Forecast error variance decomposition | Generalised forecast error variance decomposition | Using bvartools with user-written algorithms | Model set-up and prior specifications | A Gibbs sampler algorithm | bvarmodel objects | Citing bvartools | References

Introduction | The model | Imposing the restrictions | Impulse responses | Why not simply order the variables? | Variance decomposition and spillovers | Reading a set identified result | Citing bvartools | References

Introduction | Inference based on a user-written algorithm | Using the built-in simulation algorithm of bvartools | Citing bvartools | References

Introduction | Workflow for VAR models | Create a model | Adding model priors | Direct approach | Using add_priors | Adding initial values | Obtaining posterior draws | Citing bvartools | References

Introduction | Installation | Development version | Usage | Table of contents | Dataset overview | Attributes of a series | Data download | Metadata