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tsgarch: Univariate GARCH Models

Multiple flavors of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a large choice of conditional distributions. Methods for specification, estimation, prediction, filtering, simulation, statistical testing and more. Represents a partial re-write and re-think of 'rugarch', making use of automatic differentiation for estimation.

Version: 1.0.2
Depends: R (≥ 3.5.0), methods, tsmethods
Imports: TMB (≥ 1.7.20), Rcpp, nloptr, Rdpack, numDeriv, xts, zoo, future.apply, future, progressr, flextable, stats, utils, data.table, tsdistributions, lubridate, sandwich
LinkingTo: Rcpp (≥ 0.10.6), RcppArmadillo, TMB (≥ 1.7.20), RcppEigen
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-05-08
Author: Alexios Galanos [aut, cre, cph]
Maintainer: Alexios Galanos <alexios at 4dscape.com>
BugReports: https://github.com/tsmodels/tsgarch/issues
License: GPL-2
URL: https://github.com/tsmodels/tsgarch
NeedsCompilation: yes
Materials: NEWS
In views: TimeSeries
CRAN checks: tsgarch results

Documentation:

Reference manual: tsgarch.pdf
Vignettes: Benchmark
Package Demo
GARCH Models

Downloads:

Package source: tsgarch_1.0.2.tar.gz
Windows binaries: r-devel: tsgarch_1.0.2.zip, r-release: tsgarch_1.0.0.zip, r-oldrel: tsgarch_1.0.2.zip
macOS binaries: r-release (arm64): tsgarch_1.0.0.tgz, r-oldrel (arm64): tsgarch_1.0.0.tgz, r-release (x86_64): tsgarch_1.0.2.tgz, r-oldrel (x86_64): tsgarch_1.0.2.tgz
Old sources: tsgarch 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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