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GAMS Classification for the NAG C Library
NAG C Library Manual

L10a2 : Time domain analysis

g13fac    nag_estimate_agarchI
Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1+γ)2
g13fbc    nag_forecast_agarchI
Univariate time series, forecast function for either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1+γ)2
g13fcc    nag_estimate_agarchII
Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|εt-1|+γεt-1)2
g13fdc    nag_forecast_agarchII
Univariate time series, forecast function for a GARCH process with asymmetry of the form (|εt-1|+γεt-1)2
g13fec    nag_estimate_garchGJR
Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
g13ffc    nag_forecast_garchGJR
Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process

L10a2a:   Summary statistics  (3 routines)
L10a2b:   Stationarity analysis (search also class L10a2a)  (1 routine)
L10a2c:   Autoregressive models  (1 routine)
L10a2d:   ARMA and ARIMA models (including Box--Jenkins methods)  (2 routines)
L10a2e:   State-space analysis (e.g., Kalman filtering)  (6 routines)
L10a2f:   Analysis of a locally stationary series  (1 routine)

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GAMS Classification for the NAG C Library
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© The Numerical Algorithms Group Ltd, Oxford UK. 2005