_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-factorstochvol 1.1.2
Propagated dependencies: r-stochvol@3.2.9 r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1 r-gigrvg@0.8 r-corrplot@0.95
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=factorstochvol
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models
Description:

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>.

Total packages: 1