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Ch NAG Statistics

Getting Started with Ch NAG Statistics Package


g01 Simple Calculations on Statistical Data
Routine Name Purpose
g01aac nag_summary_stats_1var
Mean, variance, skewness, kurtosis, etc., one variable, from raw data
g01adc nag_summary_stats_freq
Mean, variance, skewness, kurtosis, etc., one variable, from frequency table
g01aec nag_frequency_table
Frequency table from raw data
g01alc nag_5pt_summary_stats
Five-point summary (median, hinges and extremes)
g01bjc nag_binomial_dist
Binomial distribution function
g01bkc nag_poisson_dist
Poisson distribution function
g01blc nag_hypergeom_dist
Hypergeometric distribution function
g01cec nag_deviates_normal_dist
Deviate of Normal distribution function
g01dac nag_normal_scores_exact
Normal scores, accurate values
g01dcc nag_normal_scores_var
Normal scores, approximate variance-covariance matrix
g01ddc nag_shapiro_wilk_test
Shapiro and Wilk's W test for Normality
g01dhc nag_ranks_and_scores
Ranks, Normal scores, approximate Normal scores or exponential (Savage) scores
g01eac nag_prob_normal
Probabilities for the standard Normal distribution
g01ebc nag_prob_students_t
Probabilities for Student's t-distribution
g01ecc nag_prob_chi_sq
Probabilities for χ2 distribution
g01edc nag_prob_f_dist
Probabilities for F-distribution
g01eec nag_prob_beta_dist
Upper and lower tail probabilities and probability density function for the beta distribution
g01efc nag_gamma_dist
Probabilities for the gamma distribution
g01emc nag_prob_studentized_range
Computes probability for the Studentized range statistic
g01epc nag_prob_durbin_watson
Computes bounds for the significance of a Durbin–Watson statistic
g01erc nag_prob_von_mises
Computes probability for von Mises distribution
g01etc nag_prob_landau
Landau distribution function Φ (λ)
g01euc nag_prob_vavilov
Vavilov distribution function ΦV (λ;κ,β2)
g01eyc nag_prob_1_sample_ks
Computes probabilities for the one-sample Kolmogorov–Smirnov distribution
g01ezc nag_prob_2_sample_ks
Computes probabilities for the two-sample Kolmogorov–Smirnov distribution
g01fac nag_deviates_normal
Deviates for the Normal distribution
g01fbc nag_deviates_students_t
Deviates for Student's t-distribution
g01fcc nag_deviates_chi_sq
Deviates for the χ2 distribution
g01fdc nag_deviates_f_dist
Deviates for the F-distribution
g01fec nag_deviates_beta
Deviates for the beta distribution
g01ffc nag_deviates_gamma_dist
Deviates for the gamma distribution
g01fmc nag_deviates_studentized_range
Computes deviates for the Studentized range statistic
g01ftc nag_deviates_landau
Landau inverse function Ψ (x)
g01gbc nag_prob_non_central_students_t
Computes probabilities for the non-central Student's t-distribution
g01gcc nag_prob_non_central_chi_sq
Computes probabilities for the non-central χ2 distribution
g01gdc nag_prob_non_central_f_dist
Computes probabilities for the non-central F-distribution
g01gec nag_prob_non_central_beta_dist
Computes probabilities for the non-central beta distribution
g01hac nag_bivariate_normal_dist
Probability for the bivariate Normal distribution
g01hbc nag_multi_normal
Computes probabilities for the multivariate Normal distribution
g01jcc nag_prob_lin_non_central_chi_sq
Computes probability for a positive linear combination of χ2 variables
g01jdc nag_prob_lin_chi_sq
Computes lower tail probability for a linear combination of (central) χ2 variables
g01mbc nag_mills_ratio
Computes reciprocal of Mills' Ratio
g01mtc nag_prob_density_landau
Landau density function φ (λ)
g01muc nag_prob_density_vavilov
Vavilov density function φV (λ;κ,β2)
g01nac nag_moments_quad_form
Cumulants and moments of quadratic forms in Normal variables
g01nbc nag_moments_ratio_quad_forms
Moments of ratios of quadratic forms in Normal variables, and related statistics
g01ptc nag_moment_1_landau
Landau first moment function Φ1 (x)
g01qtc nag_moment_2_landau
Landau second moment function Φ2 (x)
g01rtc nag_prob_der_landau
Landau derivative function φ ' (λ)
g01zuc nag_init_vavilov
Initialisation function for g01muc and g01euc
g02 Correlation and Regression Analysis
Routine Name Purpose
g02brc nag_ken_spe_corr_coeff
Kendall and/or Spearman non-parametric rank correlation coefficients, allows variables and observations to be selectively disregarded
g02btc nag_sum_sqs_update
Update a weighted sum of squares matrix with a new observation
g02buc nag_sum_sqs
Computes a weighted sum of squares matrix
g02bwc nag_cov_to_corr
Computes a correlation matrix from a sum of squares matrix
g02bxc nag_corr_cov
Product-moment correlation, unweighted/weighted correlation and covariance matrix, allows variables to be disregarded
g02byc nag_partial_corr
Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by g02bxc
g02cac nag_simple_linear_regression
Simple linear regression with or without a constant term, data may be weighted
g02cbc nag_regress_confid_interval
Simple linear regression confidence intervals for the regression line and individual points
g02dac nag_regsn_mult_linear
Fits a general (multiple) linear regression model
g02dcc nag_regsn_mult_linear_addrem_obs
Add/delete an observation to/from a general linear regression model
g02ddc nag_regsn_mult_linear_upd_model
Estimates of regression parameters from an updated model
g02dec nag_regsn_mult_linear_add_var
Add a new independent variable to a general linear regression model
g02dfc nag_regsn_mult_linear_delete_var
Delete an independent variable from a general linear regression model
g02dgc nag_regsn_mult_linear_newyvar
Fits a general linear regression model to new dependent variable
g02dkc nag_regsn_mult_linear_tran_model
Estimates of parameters of a general linear regression model for given constraints
g02dnc nag_regsn_mult_linear_est_func
Estimate of an estimable function for a general linear regression model
g02eac nag_all_regsn
Computes residual sums of squares for all possible linear regressions for a set of independent variables
g02ecc nag_cp_stat
Calculates R2 and CP values from residual sums of squares
g02eec nag_step_regsn
Fits a linear regression model by forward selection
g02fac nag_regsn_std_resid_influence
Calculates standardized residuals and influence statistics
g02fcc nag_durbin_watson_stat
Computes Durbin–Watson test statistic
g02gac nag_glm_normal
Fits a generalized linear model with Normal errors
g02gbc nag_glm_binomial
Fits a generalized linear model with binomial errors
g02gcc nag_glm_poisson
Fits a generalized linear model with Poisson errors
g02gdc nag_glm_gamma
Fits a generalized linear model with gamma errors
g02gkc nag_glm_tran_model
Estimates and standard errors of parameters of a general linear model for given constraints
g02gnc nag_glm_est_func
Estimable function and the standard error of a generalized linear model
g02hac nag_robust_m_regsn_estim
Robust regression, standard M-estimates
g02hbc nag_robust_m_regsn_wts
Robust regression, compute weights for use with g02hdc
g02hdc nag_robust_m_regsn_user_fn
Robust regression, compute regression with user-supplied functions and weights
g02hfc nag_robust_m_regsn_param_var
Robust regression, variance-covariance matrix following g02hdc
g02hkc nag_robust_corr_estim
Robust estimation of a correlation matrix, Huber's weight function
g02hlc nag_robust_m_corr_user_fn
Calculates a robust estimation of a correlation matrix, user-supplied weight function plus derivatives
g02hmc nag_robust_m_corr_user_fn_no_derr
Calculates a robust estimation of a correlation matrix, user-supplied weight function
g03 Multivariate Methods
Routine Name Purpose
g03aac nag_mv_prin_comp
Principal component analysis
g03acc nag_mv_canon_var
Canonical variate analysis
g03adc nag_mv_canon_corr
Canonical correlation analysis
g03bac nag_mv_orthomax
Orthogonal rotations for loading matrix
g03bcc nag_mv_procustes
Procrustes rotations
g03cac nag_mv_factor
Maximum likelihood estimates of parameters
g03ccc nag_mv_fac_score
Factor score coefficients, following g03cac
g03dac nag_mv_discrim
Test for equality of within-group covariance matrices
g03dbc nag_mv_discrim_mahaldist
Mahalanobis squared distances, following g03dac
g03dcc nag_mv_discrim_group
Allocates observations to groups, following g03dac
g03eac nag_mv_distance_mat
Compute distance (dissimilarity) matrix
g03ecc nag_mv_hierar_cluster_analysis
Hierarchical cluster analysis
g03efc nag_mv_kmeans_cluster_analysis
K-means
g03ehc nag_mv_dendrogram
Construct dendogram following g03ecc
g03ejc nag_mv_cluster_indicator
Construct clusters following g03ecc
g03fac nag_mv_prin_coord_analysis
Principal co-ordinate analysis
g03fcc nag_mv_ordinal_multidimscale
Multidimensional scaling
g03xzc nag_mv_dend_free
Frees memory allocated to the dendrogram array in g03ehc
g03zac nag_mv_z_scores
Standardize values of a data matrix
g04 Analysis of Variance Routine
Routine Name Purpose
g04bbc nag_anova_random
General block design or completely randomized design
g04bcc nag_anova_row_col
Analysis of variance, general row and column design, treatment means and standard errors
g04cac nag_anova_factorial
Complete factorial design
g04czc nag_anova_factorial_free
Memory freeing function for g04cac
g04dbc nag_anova_confid_interval
Computes confidence intervals for differences between means computed by g04bbc or g04bcc
g04eac nag_dummy_vars
Computes orthogonal polynomials or dummy variables for factor/classification variable
g05 Random Number Generators
Routine Name Purpose
g05cac nag_random_continuous_uniform
Pseudo-random real numbers, uniform distribution over (0,1)
g05cbc nag_random_init_repeatable
Initialise random number generating functions to give repeatable sequence
g05ccc nag_random_init_nonrepeatable
Initialise random number generating functions to give non-repeatable sequence
g05cfc nag_save_random_state
Save state of random number generating functions
g05cgc nag_restore_random_state
Restore state of random number generating functions
g05dac nag_random_continuous_uniform_ab
Pseudo-random real numbers, uniform distribution over (a,b)
g05dbc nag_random_exp
Pseudo-random real numbers, (negative) exponential distribution
g05ddc nag_random_normal
Pseudo-random real numbers, Normal distribution
g05dyc nag_random_discrete_uniform
Pseudo-random integer from uniform distribution
g05eac nag_ref_vec_multi_normal
Set up reference vector for multivariate Normal distribution
g05ecc nag_ref_vec_poisson
Set up reference vector for generating pseudo-random integers, Poisson distribution
g05edc nag_ref_vec_binomial
Set up reference vector for generating pseudo-random integers, binomial distribution
g05ehc nag_ran_permut_vec
Pseudo-random permutation of an integer vector
g05ejc nag_ran_sample_vec
Pseudo-random sample without replacement from an integer vector
g05exc nag_ref_vec_discrete_pdf_cdf
Set up reference vector from supplied cumulative distribution function or probability distribution function
g05eyc nag_return_discrete
Pseudo-random integer from reference vector
g05ezc nag_return_multi_normal
Pseudo-random multivariate Normal vector from reference vector
g05fec nag_random_beta
Pseudo-random real numbers from the beta distribution
g05ffc nag_random_gamma
Pseudo-random real numbers from the gamma distribution
g05hac nag_arma_time_series
ARMA time series of n terms
g05hkc nag_generate_agarchI
Univariate time series, generate n terms of either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2
g05hlc nag_generate_agarchII
Univariate time series, generate n terms of a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2
g05hmc nag_generate_garchGJR
Univariate time series, generate n terms of an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
g05kac nag_rngs_basic
Pseudo-random real numbers, uniform distribution over (0,1), seeds and generator number passed explicitly
g05kbc nag_rngs_init_repeatable
Initialise seeds of a given generator for random number generating functions (that pass seeds explicitly) to give a repeatable sequence
g05kcc nag_rngs_init_nonrepeatable
Initialise seeds of a given generator for random number generating functions (that pass seeds expicitly) to give non-repeatable sequence
g05kec nag_rngs_logical
Pseudo-random logical (boolean) value, seeds and generator number passed explicitly
g05lac nag_rngs_normal
Generates a vector of random numbers from a Normal distribution, seeds and generator number passed explicitly
g05lbc nag_rngs_students_t
Generates a vector of random numbers from a Student's t-distribution, seeds and generator number passed explicitly
g05lcc nag_rngs_chi_sq
Generates a vector of random numbers from a χ2 distribution, seeds and generator number passed explicitly
g05ldc nag_rngs_f
Generates a vector of random numbers from an F-distribution, seeds and generator number passed explicitly
g05lec nag_rngs_beta
Generates a vector of random numbers from a β distribution, seeds and generator number passed explicitly
g05lfc nag_rngs_gamma
Generates a vector of random numbers from a γ distribution, seeds and generator number passed explicitly
g05lgc nag_rngs_uniform
Generates a vector of random numbers from a uniform distribution, seeds and generator number passed explicitly
g05lhc nag_rngs_triangular
Generates a vector of random numbers from a triangular distribution, seeds and generator number passed explicitly
g05ljc nag_rngs_exp
Generates a vector of random numbers from an exponential distribution, seeds and generator number passed explicitly
g05lkc nag_rngs_lognormal
Generates a vector of random numbers from a lognormal distribution, seeds and generator number passed explicitly
g05llc nag_rngs_cauchy
Generates a vector of random numbers from a Cauchy distribution, seeds and generator number passed explicitly
g05lmc nag_rngs_weibull
Generates a vector of random numbers from a Weibull distribution, seeds and generator number passed explicitly
g05lnc nag_rngs_logistic
Generates a vector of random numbers from a logistic distribution, seeds and generator number passed explicitly
g05lpc nag_rngs_von_mises
Generates a vector of random numbers from a von Mises distribution, seeds and generator number passed explicitly
g05lqc nag_rngs_exp_mix
Generates a vector of random numbers from an exponential mixture distribution, seeds and generator number passed explicitly
g05lzc nag_rngs_multi_normal
Generates a vector of random numbers from a multivariate Normal distribution, seeds and generator number passed explicitly
g05mac nag_rngs_discrete_uniform
Generates a vector of random integers from a uniform distribution, seeds and generator number passed explicitly
g05mbc nag_rngs_geom
Generates a vector of random integers from a geometric distribution, seeds and generator number passed explicitly
g05mcc nag_rngs_neg_bin
Generates a vector of random integers from a negative binomial distribution, seeds and generator number passed explicitly
g05mdc nag_rngs_logarithmic
Generates a vector of random integers from a logarithmic distribution, seeds and generator number passed explicitly
g05mec nag_rngs_compd_poisson
Generates a vector of random integers from a Poisson distribution with varying mean, seeds and generator number passed explicitly
g05mjc nag_rngs_binomial
Generates a vector of random integers from a binomial distribution, seeds and generator number passed explicitly
g05mkc nag_rngs_poisson
Generates a vector of random integers from a Poisson distribution, seeds and generator number passed explicitly
g05mlc nag_rngs_hypergeometric
Generates a vector of random integers from a hypergeometric distribution, seeds and generator number passed explicitly
g05mrc nag_rngs_gen_multinomial
Generates a vector of random integers from a multinomial distribution, seeds and generator number passed explicitly
g05mzc nag_rngs_gen_discrete
Generates a vector of random integers from a general discrete distribution, seeds and generator number passed explicitly
g05nac nag_rngs_permute
Pseudo-random permutation of an integer vector
g05nbc nag_rngs_sample
Pseudo-random sample from an integer vector
g05pac nag_rngs_arma_time_series
Generates a realisation of a time series from an ARMA model
g05pcc nag_rngs_varma_time_series
Generates a realisation of a multivariate time series from a VARMA model
g05qac nag_rngs_orthog_matrix
Computes a random orthogonal matrix
g05qbc nag_rngs_corr_matrix
Computes a random correlation matrix
g05qdc nag_rngs_2_way_table
Generates a random table matrix
g05yac nag_quasi_random_uniform
Multi-dimensional quasi-random number generator with a uniform probability distribution
g05ybc nag_quasi_random_normal
Multi-dimensional quasi-random number generator with a Gaussian or log-normal probability distribution
g07 Univariate Estimation
Routine Name Purpose
g07aac nag_binomial_ci
Computes confidence interval for the parameter of a binomial distribution
g07abc nag_poisson_ci
Computes confidence interval for the parameter of a Poisson distribution
g07bbc nag_censored_normal
Computes maximum likelihood estimates for parameters of the Normal distribution from grouped and/or censored data
g07bec nag_estim_weibull
Computes maximum likelihood estimates for parameters of the Weibull distribution
g07cac nag_2_sample_t_test
Computes t-test statistic for a difference in means between two Normal populations, confidence interval
g07dac nag_median_1var
Robust estimation, median, median absolute deviation, robust standard deviation
g07dbc nag_robust_m_estim_1var
Robust estimation, M-estimates for location and scale parameters, standard weight functions
g07dcc nag_robust_m_estim_1var_usr
Robust estimation, M-estimates for location and scale parameters, user-defined weight functions
g07ddc nag_robust_trimmed_1var
Trimmed and winsorized mean of a sample with estimates of the variances of the two means
g07eac nag_rank_ci_1var
Robust confidence intervals, one-sample
g07ebc nag_rank_ci_2var
Robust confidence intervals, two-sample
g08 Nonparametric Statistics
Routine Name Purpose
g08aac nag_sign_test
Sign test on two paired samples
g08acc nag_median_test
Median test on two samples of unequal size
g08aec nag_friedman_test
Friedman two-way analysis of variance on k matched samples
g08afc nag_kruskal_wallis_test
Kruskal–Wallis one-way analysis of variance on k samples of unequal size
g08agc nag_wilcoxon_test
Performs the Wilcoxon one-sample (matched pairs) signed rank test
g08amc nag_mann_whitney
Performs the Mann–Whitney U test on two independent samples
g08cbc nag_1_sample_ks_test
Performs the one-sample Kolmogorov–Smirnov test for standard distributions
g08cdc nag_2_sample_ks_test
Performs the two-sample Kolmogorov–Smirnov test
g08cgc nag_chi_sq_goodness_of_fit_test
Performs the χ2 goodness of fit test, for standard continuous distributions
g08eac nag_runs_test
Performs the runs up or runs down test for randomness
g08ebc nag_pairs_test
Performs the pairs (serial) test for randomness
g08ecc nag_triplets_test
Performs the triplets test for randomness
g08edc nag_gaps_test
Performs the gaps test for randomness
g08rac nag_rank_regsn
Regression using ranks, uncensored data
g08rbc nag_rank_regsn_censored
Regression using ranks, right-censored data
g10 Smoothing in Statistics
Routine Name Purpose
g10abc nag_smooth_spline_fit
Fit cubic smoothing spline, smoothing parameter given
g10acc nag_smooth_spline_estim
Fit cubic smoothing spline, smoothing parameter estimated
g10bac nag_kernel_density_estim
Kernel density estimate using Gaussian kernel
g10cac nag_running_median_smoother
Compute smoothed data sequence using running median smoothers
g10zac nag_order_data
Reorder data to give ordered distinct observations
g11 Contingency Table Analysis
Routine Name Purpose
g11aac nag_chi_sq_2_way_table
χ2 statistics for two-way contingency table
g11bac nag_tabulate_stats
Computes multiway table from set of classification factors using selected statistic
g11bbc nag_tabulate_percentile
Computes multiway table from set of classification factors using given percentile/quantile
g11bcc nag_tabulate_margin
Computes marginal tables for multiway table computed by g11bac or g11bbc
g11cac nag_condl_logistic
Returns parameter estimates for the conditional analysis of stratified data
g11sac nag_binary_factor
Contingency table, latent variable model for binary data
g11sbc nag_binary_factor_service
Frequency count for g11sac
g12 Survival Analysis
Routine Name Purpose
g12aac nag_prod_limit_surviv_fn
Computes Kaplan–Meier (product-limit) estimates of survival probabilities
g12bac nag_surviv_cox_model
Fits Cox's proportional hazard model
g12zac nag_surviv_risk_sets
Creates the risk sets associated with the Cox proportional hazards model for fixed covariates
g13 Time Series Analysis
Routine Name Purpose
g13aac nag_tsa_diff
Univariate time series, seasonal and non-seasonal differencing
g13abc nag_tsa_auto_corr
Sample autocorrelation function
g13acc nag_tsa_auto_corr_part
Partial autocorrelation function
g13asc nag_tsa_resid_corr
Univariate time series, diagnostic checking of residuals, following g13bec
g13auc nag_tsa_mean_range
Computes quantities needed for range-mean or standard deviation-mean plot
g13bac nag_tsa_arma_filter
Multivariate time series, filtering (pre-whitening) by an ARIMA model
g13bbc nag_tsa_transf_filter
Multivariate time series, filtering by a transfer function model
g13bcc nag_tsa_cross_corr
Multivariate time series, cross-correlations
g13bdc nag_tsa_transf_prelim_fit
Multivariate time series, preliminary estimation of transfer function model
g13bec nag_tsa_multi_inp_model_estim
Estimation for time series models
g13bjc nag_tsa_multi_inp_model_forecast
Forecasting function
g13bxc nag_tsa_options_init
Initialisation function for option setting
g13byc nag_tsa_transf_orders
Allocates memory to transfer function model orders
g13bzc nag_tsa_trans_free
Freeing function for the structure holding the transfer function model orders
g13cac nag_tsa_spectrum_univar_cov
Univariate time series, smoothed sample spectrum using rectangular, Bartlett, Tukey or Parzen lag window
g13cbc nag_tsa_spectrum_univar
Univariate time series, smoothed sample spectrum using spectral smoothing by the trapezium frequency (Daniell) window
g13ccc nag_tsa_spectrum_bivar_cov
Multivariate time series, smoothed sample cross spectrum using rectangular, Bartlett, Tukey or Parzen lag window
g13cdc nag_tsa_spectrum_bivar
Multivariate time series, smoothed sample cross spectrum using spectral smoothing by the trapezium frequency (Daniell) window
g13cec nag_tsa_cross_spectrum_bivar
Multivariate time series, cross amplitude spectrum, squared coherency, bounds, univariate and bivariate (cross) spectra
g13cfc nag_tsa_gain_phase_bivar
Multivariate time series, gain, phase, bounds, univariate and bivariate (cross) spectra
g13cgc nag_tsa_noise_spectrum_bivar
Multivariate time series, noise spectrum, bounds, impulse response function and its standard error
g13dbc nag_tsa_multi_auto_corr_part
Multivariate time series, multiple squared partial autocorrelations
g13dlc nag_tsa_multi_diff
Multivariate time series, differences and/or transforms
g13dmc nag_tsa_multi_cross_corr
Multivariate time series, sample cross-correlation or cross-covariance matrices
g13dnc nag_tsa_multi_part_lag_corr
Multivariate time series, sample partial lag correlation matrices, χ2 statistics and significance levels
g13dpc nag_tsa_multi_part_regsn
Multivariate time series, partial autoregression matrices
g13dxc nag_tsa_arma_roots
Calculates the zeros of a vector autoregressive (or moving average) operator
g13eac nag_kalman_sqrt_filt_cov_var
One iteration step of the time-varying Kalman filter recursion using the square root covariance implementation
g13ebc 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 nag_kalman_sqrt_filt_info_var
One iteration step of the time-varying Kalman filter recursion using the square root information implementation
g13edc 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 nag_trans_hessenberg_observer
Unitary state-space transformation to reduce (A,C) to lower or upper observer Hessenberg form
g13exc nag_trans_hessenberg_controller
Unitary state-space transformation to reduce (B,A) to lower or upper controller Hessenberg form
g13fac 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 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 nag_estimate_agarchII
Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2
g13fdc nag_forecast_agarchII
Univariate time series, forecast function for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2
g13fec nag_estimate_garchGJR
Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
g13ffc nag_forecast_garchGJR
Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
g13xzc nag_tsa_free
Freeing function for use with g13 option setting