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> and Cadonna et al. (2020) <doi:10.3390/econometrics8020020>.

Getting started

Package details

AuthorPeter Knaus [aut, cre] (<https://orcid.org/0000-0001-6498-7084>), Angela Bitto-Nemling [aut], Annalisa Cadonna [aut] (<https://orcid.org/0000-0003-0360-7628>), Sylvia Frühwirth-Schnatter [aut] (<https://orcid.org/0000-0003-0516-5552>), Daniel Winkler [ctb], Kemal Dingic [ctb]
MaintainerPeter Knaus <peter.knaus@wu.ac.at>
LicenseGPL (>= 2)
Version2.0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("shrinkTVP")

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shrinkTVP documentation built on Nov. 10, 2020, 1:08 a.m.