Keyword : Time

G05PDF	Generates a realisation of a time series from a GARCH process with asymmetry of the form ${(ε_{t - 1} + γ)}^{2}$
G05PEF	Generates a realisation of a time series from a GARCH process with asymmetry of the form ${(\|ε_{t - 1}\| + γ ε_{t - 1})}^{2}$
G05PFF	Generates a realisation of a time series from an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
G05PGF	Generates a realisation of a time series from an exponential GARCH (EGARCH) process
G05PHF	Generates a realisation of a time series from an ARMA model
G05PJF	Generates a realisation of a multivariate time series from a VARMA model
G13AAF	Univariate time series, seasonal and non-seasonal differencing
G13ABF	Univariate time series, sample autocorrelation function
G13ACF	Univariate time series, partial autocorrelations from autocorrelations
G13ADF	Univariate time series, preliminary estimation, seasonal ARIMA model
G13AEF	Univariate time series, estimation, seasonal ARIMA model (comprehensive)
G13AFF	Univariate time series, estimation, seasonal ARIMA model (easy-to-use)
G13AGF	Univariate time series, update state set for forecasting
G13AHF	Univariate time series, forecasting from state set
G13AJF	Univariate time series, state set and forecasts, from fully specified seasonal ARIMA model
G13ASF	Univariate time series, diagnostic checking of residuals, following G13AEF or G13AFF
G13BAF	Multivariate time series, filtering (pre-whitening) by an ARIMA model
G13BBF	Multivariate time series, filtering by a transfer function model
G13BCF	Multivariate time series, cross-correlations
G13BDF	Multivariate time series, preliminary estimation of transfer function model
G13BEF	Multivariate time series, estimation of multi-input model
G13BGF	Multivariate time series, update state set for forecasting from multi-input model
G13BHF	Multivariate time series, forecasting from state set of multi-input model
G13BJF	Multivariate time series, state set and forecasts from fully specified multi-input model
G13CAF	Univariate time series, smoothed sample spectrum using rectangular, Bartlett, Tukey or Parzen lag window
G13CBF	Univariate time series, smoothed sample spectrum using spectral smoothing by the trapezium frequency (Daniell) window
G13CCF	Multivariate time series, smoothed sample cross spectrum using rectangular, Bartlett, Tukey or Parzen lag window
G13CDF	Multivariate time series, smoothed sample cross spectrum using spectral smoothing by the trapezium frequency (Daniell) window
G13CEF	Multivariate time series, cross amplitude spectrum, squared coherency, bounds, univariate and bivariate (cross) spectra
G13CFF	Multivariate time series, gain, phase, bounds, univariate and bivariate (cross) spectra
G13CGF	Multivariate time series, noise spectrum, bounds, impulse response function and its standard error
G13DBF	Multivariate time series, multiple squared partial autocorrelations
G13DDF	Multivariate time series, estimation of VARMA model
G13DJF	Multivariate time series, forecasts and their standard errors
G13DKF	Multivariate time series, updates forecasts and their standard errors
G13DLF	Multivariate time series, differences and/or transforms
G13DMF	Multivariate time series, sample cross-correlation or cross-covariance matrices
G13DNF	Multivariate time series, sample partial lag correlation matrices, $χ^{2}$ statistics and significance levels
G13DPF	Multivariate time series, partial autoregression matrices
G13DSF	Multivariate time series, diagnostic checking of residuals, following G13DDF
G13EAF	Combined measurement and time update, one iteration of Kalman filter, time-varying, square root covariance filter
G13EBF	Combined measurement and time update, one iteration of Kalman filter, time-invariant, square root covariance filter
G13FAF	Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form ${(ε_{t - 1} + γ)}^{2}$
G13FBF	Univariate time series, forecast function for either a symmetric GARCH process or a GARCH process with asymmetry of the form ${(ε_{t - 1} + γ)}^{2}$
G13FCF	Univariate time series, parameter estimation for a GARCH process with asymmetry of the form ${(\|ε_{t - 1}\| + γ ε_{t - 1})}^{2}$
G13FDF	Univariate time series, forecast function for a GARCH process with asymmetry of the form ${(\|ε_{t - 1}\| + γ ε_{t - 1})}^{2}$
G13FEF	Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
G13FFF	Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
G13FGF	Univariate time series, parameter estimation for an exponential GARCH (EGARCH) process
G13FHF	Univariate time series, forecast function for an exponential GARCH (EGARCH) process
X05AAF	Return date and time as an array of integers
X05ABF	Convert array of integers representing date and time to character string
X05ACF	Compare two character strings representing date and time
X05BAF	Return the CPU time

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NAG Library Manual