| 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 nag_tsa_multi_inp_model_estim (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 |
| g13bgc Example Text Example Data |
8 | nag_tsa_multi_inp_update Multivariate time series, update state set for forecasting from multi-input model |
| g13bjc Example Text Example Data |
2 | nag_tsa_multi_inp_model_forecast Forecasting function |
| g13bxc | 2 | nag_tsa_options_init Initialization 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 |
| g13ddc Example Text Example Data |
8 | nag_tsa_varma_estimate Multivariate time series, estimation of VARMA model |
| g13djc Example Text Example Data |
8 | nag_tsa_varma_forecast Multivariate time series, forecasts and their standard errors |
| g13dkc Example Text Example Data |
8 | nag_tsa_varma_update Multivariate time series, updates forecasts and their standard errors |
| 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 |
| g13dsc Example Text Example Data |
8 | nag_tsa_varma_diagnostic Multivariate time series, diagnostic checking of residuals, following nag_tsa_varma_estimate (g13ddc) |
| g13dxc Example Text Example Data |
7 | nag_tsa_arma_roots Calculates the zeros of a vector autoregressive (or moving average) operator |
| g13eac Example Text |
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-1B) 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|+γεt-1)2 |
| g13fdc | 6 | nag_forecast_agarchII Univariate time series, forecast function for a GARCH process with asymmetry of the form (|εt-1|+γεt-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 |