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stochvolTMB: Likelihood Estimation of Stochastic Volatility Models

Parameter estimation for stochastic volatility models using maximum likelihood. The latent log-volatility is integrated out of the likelihood using the Laplace approximation. The models are fitted via 'TMB' (Template Model Builder) (Kristensen, Nielsen, Berg, Skaug, and Bell (2016) <doi:10.18637/jss.v070.i05>).

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: TMB, ggplot2, sn, stats, data.table, MASS
LinkingTo: RcppEigen, TMB
Suggests: testthat (≥ 2.1.0), shiny, knitr, rmarkdown, stochvol
Published: 2021-08-13
Author: Jens Christian Wahl
Maintainer: Jens Christian Wahl <jens.c.wahl at gmail.com>
BugReports: https://github.com/JensWahl/stochvolTMB/issues
License: GPL-3
URL: https://github.com/JensWahl/stochvolTMB
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: stochvolTMB results

Documentation:

Reference manual: stochvolTMB.pdf
Vignettes: stochvolTMB: Likelihood estimation of stochastic volatility

Downloads:

Package source: stochvolTMB_0.2.0.tar.gz
Windows binaries: r-devel: stochvolTMB_0.2.0.zip, r-release: stochvolTMB_0.2.0.zip, r-oldrel: stochvolTMB_0.2.0.zip
macOS binaries: r-release (arm64): stochvolTMB_0.2.0.tgz, r-oldrel (arm64): stochvolTMB_0.2.0.tgz, r-release (x86_64): stochvolTMB_0.2.0.tgz, r-oldrel (x86_64): stochvolTMB_0.2.0.tgz
Old sources: stochvolTMB archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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