fGarch

Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

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

Total

389,363

Last month

13,552

Last week

3,320

Average per day

452

Daily downloads

Total downloads

Description file content

Package
fGarch
Title
Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Date
2017-11-12
Version
3042.83.1
Author
Diethelm Wuertz [aut], Tobias Setz [cre], Yohan Chalabi [ctb], Chris Boudt [ctb], Pierre Chausse [ctb], Michal Miklovac [ctb]
Maintainer
Tobias Setz
Description
Provides a collection of functions to analyze and model heteroskedastic behavior in financial time series models.
Depends
R (>= 2.15.1), timeDate, timeSeries, fBasics
Imports
fastICA, Matrix, graphics, methods, stats, utils
Suggests
RUnit, tcltk
LazyData
yes
License
GPL (>= 2)
URL
NeedsCompilation
yes
Packaged
2019-01-31 16:42:21 UTC; hornik
Repository
CRAN
Date/Publication
2019-01-31 17:27:52 UTC

install.packages('fGarch')

3042.83.1

9 months ago

https://www.rmetrics.org

Tobias Setz

GPL (>= 2)

Depends on

R (>= 2.15.1), timeDate, timeSeries, fBasics

Imports

fastICA, Matrix, graphics, methods, stats, utils

Suggests

RUnit, tcltk

Discussions