Efficient Bayesian Inference for Time-Varying Parameter Models
with Shrinkage
Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors, both dynamic and static. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) and
Cadonna et al. (2020) and Knaus and Frühwirth-Schnatter (2023) . For details on the package, please see Knaus et al. (2021) . For the multivariate extension, see the 'shrinkTVPVAR' package.