fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling (original) (raw)

Analyze and model heteroskedastic behavior in financial time series.

Version:

4033.92

Imports:

fBasics, timeDate, timeSeries, fastICA, Matrix (≥ 1.5-0), cvar (≥ 0.5), graphics, methods, stats, utils

Suggests:

RUnit, tcltk, goftest

Published:

2024-03-26

DOI:

10.32614/CRAN.package.fGarch

Author:

Diethelm Wuertz [aut] (original code), Yohan Chalabi [aut], Tobias Setz [aut], Martin Maechler [aut], Chris Boudt [ctb], Pierre Chausse [ctb], Michal Miklovac [ctb], Georgi N. Boshnakov [aut, cre]

Maintainer:

Georgi N. Boshnakov <georgi.boshnakov at manchester.ac.uk>

BugReports:

https://r-forge.r-project.org/projects/rmetrics

License:

GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]

URL:

https://geobosh.github.io/fGarchDoc/ (doc),https://www.rmetrics.org (devel)

NeedsCompilation:

yes

Materials:

README NEWS

In views:

Finance, TimeSeries

CRAN checks:

fGarch results