CRAN/E | shrinkTVP

shrinkTVP

Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage

Installation

About

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) doi:10.1016/j.jeconom.2018.11.006 and Cadonna et al. (2020) doi:10.3390/econometrics8020020 and Knaus and Frühwirth-Schnatter (2023) doi:10.48550/arXiv.2312.10487. For details on the package, please see Knaus et al. (2021) doi:10.18637/jss.v100.i13.

Citation shrinkTVP citation info

Key Metrics

Version 3.0.1
R ≥ 3.3.0
Published 2024-02-18 78 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks shrinkTVP results

Downloads

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Maintainer

Maintainer

Peter Knaus

peter.knaus@wu.ac.at

Authors

Peter Knaus

aut / cre

Angela Bitto-Nemling

aut

Annalisa Cadonna

aut

Sylvia Frühwirth-Schnatter

aut

Daniel Winkler

ctb

Kemal Dingic

ctb

Material

NEWS
Reference manual
Package source

In Views

Bayesian

Vignettes

Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

shrinkTVP archive

Depends

R ≥ 3.3.0

Imports

Rcpp
GIGrvg
stochvol ≥ 3.0.3
coda
methods
utils
zoo

Suggests

testthat
knitr
rmarkdown
R.rsp

LinkingTo

Rcpp
RcppArmadillo
GIGrvg
RcppProgress
stochvol
RcppGSL

Reverse Imports

shrinkDSM

Reverse Suggests

tidyfit

Reverse LinkingTo

shrinkDSM