fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

Provides a collection of functions to analyze and model heteroskedastic behavior in financial time series models.

Version: 3042.83.2
Depends: R (≥ 2.15.1), timeDate, timeSeries, fBasics
Imports: fastICA, Matrix, graphics, methods, stats, utils
Suggests: RUnit, tcltk
Published: 2020-03-07
Author: Diethelm Wuertz [aut], Tobias Setz [cre], Yohan Chalabi [ctb], Chris Boudt [ctb], Pierre Chausse [ctb], Michal Miklovac [ctb]
Maintainer: Tobias Setz <tobias.setz at live.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.rmetrics.org
NeedsCompilation: yes
Materials: ChangeLog
In views: Finance, TimeSeries
CRAN checks: fGarch results


Reference manual: fGarch.pdf


Package source: fGarch_3042.83.2.tar.gz
Windows binaries: r-devel: fGarch_3042.83.2.zip, r-release: fGarch_3042.83.2.zip, r-oldrel: fGarch_3042.83.2.zip
macOS binaries: r-release (arm64): fGarch_3042.83.2.tgz, r-release (x86_64): fGarch_3042.83.2.tgz, r-oldrel: fGarch_3042.83.2.tgz
Old sources: fGarch archive

Reverse dependencies:

Reverse depends: distrRmetrics, fExtremes, gogarch, mleur
Reverse imports: cvar, ftsa, gscreend, GWEX, IndexConstruction, irtDemo, L2DensityGoFtest, ludic, mixAR, segMGarch, univariateML
Reverse suggests: AER, CLA, fPortfolio, ggfortify, gratis, portes, PortfolioAnalytics, sarima, simsalapar, smoots, symmetry
Reverse enhances: stargazer, texreg


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