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>.

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Description file content

Package
shrinkTVP
Type
Package
Title
Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
Version
1.0.2
Description
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) .
License
GPL (>= 2)
Encoding
UTF-8
LazyData
true
Depends
R (>= 3.3.0)
Imports
Rcpp, GIGrvg, stochvol, coda, methods, utils
LinkingTo
Rcpp, RcppArmadillo, GIGrvg, RcppProgress, stochvol
RoxygenNote
6.1.1
Suggests
testthat, knitr, rmarkdown, R.rsp
VignetteBuilder
R.rsp
NeedsCompilation
yes
Packaged
2019-08-07 13:34:17 UTC; pknaus
Author
Peter Knaus [aut, cre] (), Angela Bitto-Nemling [aut], Annalisa Cadonna [aut] (), Sylvia Frühwirth-Schnatter [aut] (), Daniel Winkler [ctb], Kemal Dingic [ctb]
Maintainer
Peter Knaus
Repository
CRAN
Date/Publication
2019-08-07 14:40:02 UTC

install.packages('shrinkTVP')

1.0.2

14 days ago

Peter Knaus

GPL (>= 2)

Depends on

R (>= 3.3.0)

Imports

Rcpp, GIGrvg, stochvol, coda, methods, utils

Suggests

testthat, knitr, rmarkdown, R.rsp

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