Chapter Introduction (pdf version)
NAG C Library Manual

g13 – Time Series Analysis

g13 Chapter Introduction
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

Chapter Introduction (pdf version)
NAG C Library Manual

The Numerical Algorithms Group Ltd, Oxford, UK. 2005