factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models

Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models with interweaving <doi:10.1080/10618600.2017.1322091>. Sparsity can be achieved through the usage of Normal-Gamma priors on the factor loading matrix <doi:10.1016/j.jeconom.2018.11.007>.

Version: 0.9.2
Depends: R (≥ 3.0.2), stochvol (≥ 2.0.4)
Imports: GIGrvg (≥ 0.4), Rcpp (≥ 1.0.0), corrplot, methods, grDevices, graphics, stats, utils
LinkingTo: Rcpp, RcppArmadillo (≥ 0.7.500.0.0), stochvol
Suggests: LSD (≥ 4.0-0), coda (≥ 0.19-2), knitr, RColorBrewer
Published: 2019-06-27
Author: Gregor Kastner ORCID iD [aut, cre], Darjus Hosszejni ORCID iD [ctb]
Maintainer: Gregor Kastner <gregor.kastner at wu.ac.at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: factorstochvol citation info
Materials: NEWS
In views: Finance, TimeSeries
CRAN checks: factorstochvol results


Reference manual: factorstochvol.pdf
Vignettes: Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
Package source: factorstochvol_0.9.2.tar.gz
Windows binaries: r-devel: factorstochvol_0.9.2.zip, r-release: factorstochvol_0.9.2.zip, r-oldrel: factorstochvol_0.9.2.zip
OS X binaries: r-release: factorstochvol_0.9.2.tgz, r-oldrel: factorstochvol_0.9.2.tgz
Old sources: factorstochvol archive


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