Routine Name |
Mark of Introduction |
Purpose |
g13aac
Example Text Example Data |
7 |
nag_tsa_diff
Univariate time series, seasonal and non-seasonal differencing |
g13abc
Example Text Example Data |
2 |
nag_tsa_auto_corr
Sample autocorrelation function |
g13acc
Example Text Example Data |
2 |
nag_tsa_auto_corr_part
Partial autocorrelation function |
g13asc
Example Text Example Data |
6 |
nag_tsa_resid_corr
Univariate time series, diagnostic checking of residuals, following g13bec |
g13auc
Example Text Example Data |
7 |
nag_tsa_mean_range
Computes quantities needed for range-mean or standard deviation-mean plot |
g13bac
Example Text Example Data |
7 |
nag_tsa_arma_filter
Multivariate time series, filtering (pre-whitening) by an ARIMA model |
g13bbc
Example Text Example Data |
7 |
nag_tsa_transf_filter
Multivariate time series, filtering by a transfer function model |
g13bcc
Example Text Example Data |
7 |
nag_tsa_cross_corr
Multivariate time series, cross-correlations |
g13bdc
Example Text Example Data |
7 |
nag_tsa_transf_prelim_fit
Multivariate time series, preliminary estimation of transfer function model |
g13bec
Example Text Example Data |
2 |
nag_tsa_multi_inp_model_estim
Estimation for time series models |
g13bjc
Example Text Example Data |
2 |
nag_tsa_multi_inp_model_forecast
Forecasting function |
g13bxc | 2 |
nag_tsa_options_init
Initialisation function for option setting |
g13byc | 2 |
nag_tsa_transf_orders
Allocates memory to transfer function model orders |
g13bzc | 2 |
nag_tsa_trans_free
Freeing function for the structure holding the transfer function model orders |
g13cac
Example Text Example Data |
7 |
nag_tsa_spectrum_univar_cov
Univariate time series, smoothed sample spectrum using rectangular, Bartlett, Tukey or Parzen lag window |
g13cbc
Example Text Example Data |
4 |
nag_tsa_spectrum_univar
Univariate time series, smoothed sample spectrum using spectral smoothing by the trapezium frequency (Daniell) window |
g13ccc
Example Text Example Data |
7 |
nag_tsa_spectrum_bivar_cov
Multivariate time series, smoothed sample cross spectrum using rectangular, Bartlett, Tukey or Parzen lag window |
g13cdc
Example Text Example Data |
4 |
nag_tsa_spectrum_bivar
Multivariate time series, smoothed sample cross spectrum using spectral smoothing by the trapezium frequency (Daniell) window |
g13cec
Example Text Example Data |
4 |
nag_tsa_cross_spectrum_bivar
Multivariate time series, cross amplitude spectrum, squared coherency, bounds, univariate and bivariate (cross) spectra |
g13cfc
Example Text Example Data |
4 |
nag_tsa_gain_phase_bivar
Multivariate time series, gain, phase, bounds, univariate and bivariate (cross) spectra |
g13cgc
Example Text Example Data |
4 |
nag_tsa_noise_spectrum_bivar
Multivariate time series, noise spectrum, bounds, impulse response function and its standard error |
g13dbc
Example Text Example Data |
7 |
nag_tsa_multi_auto_corr_part
Multivariate time series, multiple squared partial autocorrelations |
g13dlc
Example Text Example Data |
7 |
nag_tsa_multi_diff
Multivariate time series, differences and/or transforms |
g13dmc
Example Text Example Data |
7 |
nag_tsa_multi_cross_corr
Multivariate time series, sample cross-correlation or cross-covariance matrices |
g13dnc
Example Text Example Data |
7 |
nag_tsa_multi_part_lag_corr
Multivariate time series, sample partial lag correlation matrices, χ2 statistics and significance levels |
g13dpc
Example Text Example Data |
7 |
nag_tsa_multi_part_regsn
Multivariate time series, partial autoregression matrices |
g13dxc
Example Text Example Data |
7 |
nag_tsa_arma_roots
Calculates the zeros of a vector autoregressive (or moving average) operator |
g13eac
Example Text Example Data |
3 |
nag_kalman_sqrt_filt_cov_var
One iteration step of the time-varying Kalman filter recursion using the square root covariance implementation |
g13ebc
Example Text Example Data |
3 |
nag_kalman_sqrt_filt_cov_invar
One iteration step of the time-invariant Kalman filter recursion using the square root covariance implementation with (A,C) in lower observer Hessenberg form |
g13ecc
Example Text Example Data |
3 |
nag_kalman_sqrt_filt_info_var
One iteration step of the time-varying Kalman filter recursion using the square root information implementation |
g13edc
Example Text Example Data |
3 |
nag_kalman_sqrt_filt_info_invar
One iteration step of the time-invariant Kalman filter recursion using the square root information implementation with (A-1, A-1 B) in upper controller Hessenberg form |
g13ewc
Example Text Example Data |
3 |
nag_trans_hessenberg_observer
Unitary state-space transformation to reduce (A,C) to lower or upper observer Hessenberg form |
g13exc
Example Text Example Data |
3 |
nag_trans_hessenberg_controller
Unitary state-space transformation to reduce (B,A) to lower or upper controller Hessenberg form |
g13fac
Example Text |
6 |
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 | 6 |
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
Example Text |
6 |
nag_estimate_agarchII
Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
g13fdc | 6 |
nag_forecast_agarchII
Univariate time series, forecast function for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
g13fec
Example Text |
6 |
nag_estimate_garchGJR
Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
g13ffc | 6 |
nag_forecast_garchGJR
Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
g13xzc | 2 |
nag_tsa_free
Freeing function for use with g13 option setting |