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fGarch (version 4021.88)

Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

Description

Analyze and model heteroskedastic behavior in financial time series.

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Version

Install

install.packages('fGarch')

Monthly Downloads

14,321

Version

4021.88

License

GPL (>= 2)

Maintainer

Georgi Boshnakov

Last Published

September 29th, 2022

Functions in fGarch (4021.88)

fGarch-package

Modelling Heterskedasticity in Financial Time Series
snormFit

Skew Normal Distribution Parameter Estimation
snormSlider

Skew Normal Distribution Slider
sgedFit

Skew Generalized Error Distribution Parameter Estimation
fGARCH-class

Class "fGARCH"
gedSlider

Generalized Error Distribution Slider
gedFit

Generalized Error Distribution Parameter Estimation
sstd

Skew Student-t Distribution and Parameter Estimation
predict-methods

GARCH Prediction Function
ged

Generalized Error Distribution
sstdFit

Skew Student-t Distribution Parameter Estimation
snorm

Skew Normal Distribution
sgedSlider

Skew GED Distribution Slider
stdSlider

Student-t Distribution Slider
formula-methods

Extract GARCH Model formula
stdFit

Student-t Distribution Parameter Estimation
sstdSlider

Skew Student-t Distribution Slider
std

Student-t Distribution
garchSim

Univariate GARCH/APARCH Time Series Simulation
residuals-methods

Extract GARCH Model Residuals
coef-methods

GARCH Coefficients Methods
volatility-methods

Extract GARCH Model Volatility
fitted-methods

Extract GARCH Model Fitted Values
garchFit

Univariate or Multivariate GARCH Time Series Fitting
plot-methods

GARCH Plot Methods
garchSpec

Univariate GARCH Time Series Specification
summary-methods

GARCH Summary Methods
show-methods

GARCH Modelling Show Methods
garchFitControl

GARCH Fitting Algorithms and Control
sged

Skew Generalized Error Distribution
absMoments

Absolute Moments of GARCH Distributions
fGARCHSPEC-class

Class "fGARCHSPEC"
TimeSeriesData

Time Series Data Sets