NAG Toolbox |

- G13 Introduction
- g13aa – Univariate time series, seasonal and non-seasonal differencing
- nag_tsa_uni_diff – g13aa
- g13ab – Univariate time series, sample autocorrelation function
- nag_tsa_uni_autocorr – g13ab
- g13ac – Univariate time series, partial autocorrelations from autocorrelations
- nag_tsa_uni_autocorr_part – g13ac
- g13ad – Univariate time series, preliminary estimation, seasonal ARIMA model
- nag_tsa_uni_arima_prelim – g13ad
- g13ae – Univariate time series, estimation, seasonal ARIMA model (comprehensive)
- nag_tsa_uni_arima_estim – g13ae
- g13af – Univariate time series, estimation, seasonal ARIMA model (easy-to-use)
- nag_tsa_uni_arima_estim_easy – g13af
- g13ag – Univariate time series, update state set for forecasting
- nag_tsa_uni_arima_update – g13ag
- g13ah – Univariate time series, forecasting from state set
- nag_tsa_uni_arima_forecast_state – g13ah
- g13aj – Univariate time series, state set and forecasts, from fully specified seasonal ARIMA model
- nag_tsa_uni_arima_forcecast – g13aj
- g13am – Univariate time series, exponential smoothing
- nag_tsa_uni_smooth_exp – g13am
- g13as – Univariate time series, diagnostic checking of residuals, following g13ae or g13af
- nag_tsa_uni_arima_resid – g13as
- g13au – Computes quantities needed for range-mean or standard deviation-mean plot
- nag_tsa_uni_means – g13au
- g13ba – Multivariate time series, filtering (pre-whitening) by an ARIMA model
- nag_tsa_multi_filter_arima – g13ba
- g13bb – Multivariate time series, filtering by a transfer function model
- nag_tsa_multi_filter_transf – g13bb
- g13bc – Multivariate time series, cross-correlations
- nag_tsa_multi_xcorr – g13bc
- g13bd – Multivariate time series, preliminary estimation of transfer function model
- nag_tsa_multi_transf_prelim – g13bd
- g13be – Multivariate time series, estimation of multi-input model
- nag_tsa_multi_inputmod_estim – g13be
- g13bg – Multivariate time series, update state set for forecasting from multi-input model
- nag_tsa_multi_inputmod_update – g13bg
- g13bh – Multivariate time series, forecasting from state set of multi-input model
- nag_tsa_multi_inputmod_forecast_state – g13bh
- g13bj – Multivariate time series, state set and forecasts from fully specified multi-input model
- nag_tsa_multi_inputmod_forecast – g13bj
- g13ca – Univariate time series, smoothed sample spectrum using rectangular, Bartlett, Tukey or Parzen lag window
- nag_tsa_uni_spectrum_lag – g13ca
- g13cb – Univariate time series, smoothed sample spectrum using spectral smoothing by the trapezium frequency (Daniell) window
- nag_tsa_uni_spectrum_daniell – g13cb
- g13cc – Multivariate time series, smoothed sample cross spectrum using rectangular, Bartlett, Tukey or Parzen lag window
- nag_tsa_multi_spectrum_lag – g13cc
- g13cd – Multivariate time series, smoothed sample cross spectrum using spectral smoothing by the trapezium frequency (Daniell) window
- nag_tsa_multi_spectrum_daniell – g13cd
- g13ce – Multivariate time series, cross amplitude spectrum, squared coherency, bounds, univariate and bivariate (cross) spectra
- nag_tsa_multi_spectrum_bivar – g13ce
- g13cf – Multivariate time series, gain, phase, bounds, univariate and bivariate (cross) spectra
- nag_tsa_multi_gain_bivar – g13cf
- g13cg – Multivariate time series, noise spectrum, bounds, impulse response function and its standard error
- nag_tsa_multi_noise_bivar – g13cg
- g13db – Multivariate time series, multiple squared partial autocorrelations
- nag_tsa_multi_autocorr_part – g13db
- g13dd – Multivariate time series, estimation of VARMA model
- nag_tsa_multi_varma_estimate – g13dd
- g13dj – Multivariate time series, forecasts and their standard errors
- nag_tsa_multi_varma_forecast – g13dj
- g13dk – Multivariate time series, updates forecasts and their standard errors
- nag_tsa_multi_varma_update – g13dk
- g13dl – Multivariate time series, differences and/or transforms
- nag_tsa_multi_diff – g13dl
- g13dm – Multivariate time series, sample cross-correlation or cross-covariance matrices
- nag_tsa_multi_corrmat_cross – g13dm
- g13dn – Multivariate time series, sample partial lag correlation matrices, chi ^2 statistics and significance levels
- nag_tsa_multi_corrmat_partlag – g13dn
- g13dp – Multivariate time series, partial autoregression matrices
- nag_tsa_multi_regmat_partial – g13dp
- g13ds – Multivariate time series, diagnostic checking of residuals, following g13dd
- nag_tsa_multi_varma_diag – g13ds
- g13dx – Calculates the zeros of a vector autoregressive (or moving average) operator
- nag_tsa_uni_arma_roots – g13dx
- g13ea – Combined measurement and time update, one iteration of Kalman filter, time-varying, square root covariance filter
- nag_tsa_multi_kalman_sqrt_var – g13ea
- g13eb – Combined measurement and time update, one iteration of Kalman filter, time-invariant, square root covariance filter
- nag_tsa_multi_kalman_sqrt_invar – g13eb
- g13fa – Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form ( epsilon _t-1+ gamma )^2
- nag_tsa_uni_garch_asym1_estim – g13fa
- g13fb – Univariate time series, forecast function for either a symmetric GARCH process or a GARCH process with asymmetry of the form ( epsilon _t-1+ gamma )^2
- nag_tsa_uni_garch_asym1_forecast – g13fb
- g13fc – Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (| epsilon _t-1|+ gamma epsilon _t-1)^2
- nag_tsa_uni_garch_asym2_estim – g13fc
- g13fd – Univariate time series, forecast function for a GARCH process with asymmetry of the form (| epsilon _t-1|+ gamma epsilon _t-1)^2
- nag_tsa_uni_garch_asym2_forecast – g13fd
- g13fe – Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
- nag_tsa_uni_garch_gjr_estim – g13fe
- g13ff – Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
- nag_tsa_uni_garch_gjr_forecast – g13ff
- g13fg – Univariate time series, parameter estimation for an exponential GARCH (EGARCH) process
- nag_tsa_uni_garch_exp_estim – g13fg
- g13fh – Univariate time series, forecast function for an exponential GARCH (EGARCH) process
- nag_tsa_uni_garch_exp_forecast – g13fh
- g13me – Computes the iterated exponential moving average for a univariate inhomogeneous time series
- nag_tsa_inhom_iema – g13me
- g13mf – Computes the iterated exponential moving average for a univariate inhomogeneous time series, intermediate results are also returned
- nag_tsa_inhom_iema_all – g13mf
- g13mg – Computes the exponential moving average for a univariate inhomogeneous time series
- nag_tsa_inhom_ma – g13mg

G12 |
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