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
Depends: R (≥ 2.15.1), timeDate, timeSeries, fBasics
Imports: fastICA, Matrix, graphics, methods, stats, utils
Suggests: RUnit, tcltk
Published: 2017-11-16
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.tar.gz
Windows binaries: r-devel: fGarch_3042.83.zip, r-release: fGarch_3042.83.zip, r-oldrel: fGarch_3042.83.zip
OS X El Capitan binaries: r-release: fGarch_3042.83.tgz
OS X Mavericks binaries: r-oldrel: fGarch_3042.83.tgz
Old sources: fGarch archive

Reverse dependencies:

Reverse depends: DAC, distrRmetrics, fExtremes, gogarch, mleur
Reverse imports: covmat, GEVStableGarch, irtDemo, ludic, MTS
Reverse suggests: AER, caschrono, CLA, fPortfolio, ggfortify, portes, PortfolioAnalytics, sarima, simsalapar
Reverse enhances: stargazer, texreg


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