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tsmarch: Multivariate ARCH Models

Feasible Multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models including Dynamic Conditional Correlation (DCC), Copula GARCH and Generalized Orthogonal GARCH with Generalized Hyperbolic distribution. A review of some of these models can be found in Boudt, Galanos, Payseur and Zivot (2019) <doi:10.1016/bs.host.2019.01.001>.

Version: 1.0.0
Depends: R (≥ 3.5.0), methods, tsmethods (≥ 1.0.2)
Imports: Rcpp, RcppParallel, tsgarch (≥ 1.0.3), tsdistributions (≥ 1.0.2), RcppBessel, Rsolnp, nloptr, numDeriv, abind, shape, Rdpack, xts, zoo, lubridate, sandwich, future.apply, future, stats, utils, data.table
LinkingTo: Rcpp (≥ 0.10.6), RcppArmadillo, RcppParallel, RcppBessel
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), tstests
Published: 2024-11-18
DOI: 10.32614/CRAN.package.tsmarch
Author: Alexios Galanos ORCID iD [aut, cre, cph]
Maintainer: Alexios Galanos <alexios at 4dscape.com>
BugReports: https://github.com/tsmodels/tsmarch/issues
License: GPL-2
URL: https://github.com/tsmodels/tsmarch, https://www.nopredict.com
NeedsCompilation: yes
SystemRequirements: GNU make
In views: TimeSeries
CRAN checks: tsmarch results

Documentation:

Reference manual: tsmarch.pdf
Vignettes: Feasible Multivariate GARCH Models (source, R code)
tsmarch demo (source, R code)

Downloads:

Package source: tsmarch_1.0.0.tar.gz
Windows binaries: r-devel: tsmarch_1.0.0.zip, r-release: tsmarch_1.0.0.zip, r-oldrel: tsmarch_1.0.0.zip
macOS binaries: r-release (arm64): tsmarch_1.0.0.tgz, r-oldrel (arm64): tsmarch_1.0.0.tgz, r-release (x86_64): tsmarch_1.0.0.tgz, r-oldrel (x86_64): tsmarch_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=tsmarch to link to this page.

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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