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GAS

GAS implements the Generalized Autoregressive Score (GAS) framework in R. The GAS package provides functions to simulate univariate and multivariate GAS processes, estimate the GAS parameters and to make time series forecasts. Full description of the algorithm and numerous applications are available in Ardia et al. (2018) and Ardia et al. (2019).

Please cite the package in publications!

By using GAS you agree to the following rules:

  1. You must cite Ardia et al. (2019) in working papers and published papers that use GAS.
  2. You must place the following URL in a footnote to help others find GAS: https://CRAN.R-project.org/package=GAS.
  3. You assume all risk for the use of GAS.

Ardia, D., Boudt, K., Catania, L. (2018).
Downside Risk Evaluation with the R Package GAS.
R Journal, 10(2), 410-421.
https://doi.org/10.32614/RJ-2018-064

Ardia, D., Boudt, K., Catania, L. (2019).
Generalized autoregressive score models in R: The GAS package.
Journal of Statistical Software, 88(6), 1-28.
https://doi.org/10.18637/jss.v088.i06

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Version

Install

install.packages('GAS')

Monthly Downloads

741

Version

0.3.4.1

License

GPL-3

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Last Published

August 19th, 2024

Functions in GAS (0.3.4.1)

MultiMapParameters

Mapping function for univariate distributions
UniGASFor

Forecast with univariate GAS models
PIT_test

Goodness of fit for conditional densities
UniGASFit

Estimate univariate GAS models
MultiGASFor

Forecast with multivariate GAS models
MultiGASSim

Simulate multivariate GAS processes
MultiGASRoll

Rolling forecast with multivariate GAS models
StockIndices

Data: Daily logarithmic returns in percentage points of the DAX, FTSEMIB and CAC40 from 2007-01-03 to 2016-06-24
MultiUnmapParameters

Inverse of MultiMapParameters
MultiGASSpec

Multivariate GAS specification
UniMapParameters

Mapping function for univariate distributions
fn.solnp

A wrapper to the solnp function of the Rsolnp package of Ghalanos and Theussl (2016).
fn.optim

dji30ret

data: Dow Jones 30 Constituents Closing Value Log Return in percentage points
UniGASRoll

Rolling forecast with univariate GAS models
UniGASSim

Simulate Univariate GAS processes
UniGASSpec

Univariate GAS specification
UniUnmapParameters

Unmapping function for univariate distributions, i.e. inverse of UniMapParameters
cpichg

Data: Quarterly logarithmic change in percentage points of the Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) from 1947-04-01 to 2016-05-01
mGASFit

Class for the Multivariate GAS fitted object
sp500rv

Data: SP500 Daily 5 minutes Realized Volatility from 2000-01-03 to 2000-01-10
plot-methods

Plot output from an object of the from the GAS package.
sp500ret

Data: Daily logarithmic returns in percentage points of the S&P500 index from 1950-01-04 to 2016-06-24
mGASRoll

Class for the Multivariate GAS Rolling object
mGASSpec

Class for the Multivariate GAS model specification
mGASSim

Class for Multivariate GAS Simulation
mGASFor

Class for the Multivariate GAS Forecast object
uGASFit

Class for the univariate GAS fitted object
uGASRoll

Class for the univariate GAS rolling object
uGASFor

Class for the univariate GAS forecast object
usunp

US Monthly Civilian Unemployment Rate (UNRATE) from 1948-01-01 to 2016-05-01
uGASSpec

Class for the univariate GAS model specification
tqdata

Data from Bien et al (2011).
uGASSim

Class for Univariate GAS Simulation
Goals

data: Goals scored by England against Scotland in international football matches.
MultiGASFit

Estimate multivariate GAS models
BacktestVaR

Backtest Value at Risk (VaR)
distributions

Distributions of the GAS package
BacktestDensity

Backtest a series of one-step ahead density predictions.
NumericalBounds

Numerical bounds imposed in parameters transformation.
ConfidenceBands

Build confidence bands for the filtered parameters
FZLoss

Fissler and Ziegel (2016) (FZ) joint loss function for Value at Risk and Expected Shortfall.
DistInfo

Information for the supported distributions
GAS-package

Generalized Autoregressive Score models in R