R: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage

# Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage

## Documentation for package ‘shrinkTVP’ version 3.1.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

eval_pred_dens | Evaluate the one-step ahead predictive density of a fitted TVP model
fitted.shrinkTVP | Calculate fitted historical values for an estimated TVP model
forecast_shrinkTVP | Draw from posterior predictive density of a fitted TVP model
LPDS | Calculate the Log Predictive Density Score for a fitted TVP model
plot.mcmc.tvp | Graphical summary of posterior distribution for a time-varying parameter
plot.shrinkTVP | Graphical summary of posterior distribution
plot.shrinkTVP_forc | Graphical summary of posterior predictive density
predict.shrinkTVP | Calculate predicted historical values for an estimated TVP model
print.shrinkTVP | Nicer printing of shrinkTVP objects
residuals.shrinkTVP | Calculate residuals for an estimated TVP model
shrinkDTVP | Markov Chain Monte Carlo (MCMC) for time-varying parameter models with dynamic shrinkage
shrinkTVP | Markov Chain Monte Carlo (MCMC) for time-varying parameter models with shrinkage
simTVP | Generate synthetic data from a time-varying parameter model
updateTVP | One step update version of 'shrinkTVP' with minimal overhead