swMATH ID: 29787
Software Authors: Peter Knaus, Angela Bitto-Nemling , Annalisa Cadonna, Sylvia Frühwirth-Schnatter, Daniel Winkler, Kemal Dingic
Description: R package shrinkTVP: 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. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006>.
Homepage: https://cran.r-project.org/web/packages/shrinkTVP/index.html
Source Code:  https://github.com/cran/shrinkTVP
Dependencies: R
Keywords: Econometrics; arXiv_econ.EM; arXiv_stat.CO; R; R package; time-varying parameter; TVP; Bayesian inference; Gibbs sampler; Markov chain Monte Carlo; MCMC; normal-gamma prior; log predictive density scores
Related Software: R; zoo; CODA; RcppArmadillo; Rcpp; stochvol; tibble; CmdStan; pder; loo; posterior; ggplot2; tvem; fixest; dynamite; FENmlm; data.table; CmdStanR; RStan; pomp
Cited in: 1 Document

Standard Articles

1 Publication describing the Software Year
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP
Angela Bitto-Nemling, Annalisa Cadonna, Sylvia Frühwirth-Schnatter, Peter Knaus

Cited in 1 Serial

1 Open Economies Review

Citations by Year