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NAG Toolbox
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New Functions

The new user-callable functions included in the NAG Toolbox at Mark 24 are as follows.
Function
Name

Purpose
nag_sum_fft_real_2d (c06pv)Two-dimensional real-to-complex discrete Fourier transform
nag_sum_fft_hermitian_2d (c06pw)Two-dimensional complex-to-real discrete Fourier transform
nag_sum_fft_real_3d (c06py)Three-dimensional real-to-complex discrete Fourier transform
nag_sum_fft_hermitian_3d (c06pz)Three-dimensional complex-to-real discrete Fourier transform
nag_wav_3d_init (c09ac)Three-dimensional wavelet filter initialization
nag_wav_3d_sngl_fwd (c09fa)Three-dimensional discrete wavelet transform
nag_wav_3d_sngl_inv (c09fb)Three-dimensional inverse discrete wavelet transform
nag_wav_3d_multi_fwd (c09fc)Three-dimensional multi-level discrete wavelet transform
nag_wav_3d_mxolap_multi_inv (c09fd)Three-dimensional inverse multi-level discrete wavelet transform
nag_quad_1d_gen_vec_multi_rcomm (d01ra)One-dimensional quadrature, adaptive, finite interval, multiple integrands, vectorized abscissae, reverse communication
nag_quad_1d_gen_vec_multi_dimreq (d01rc)Determine required array dimensions for nag_quad_1d_gen_vec_multi_rcomm (d01ra)
nag_quad_1d_fin_gonnet_vec (d01rg)One-dimensional quadrature, adaptive, finite interval, strategy due to Gonnet, allowing for badly behaved integrands
nag_quad_1d_gauss_wres (d01tb)Pre-computed weights and abscissae for Gaussian quadrature rules, restricted choice of rule
nag_quad_1d_gauss_vec (d01ua)One-dimensional Gaussian quadrature, choice of weight functions
nag_quad_opt_set (d01zk)Option setting function
nag_quad_opt_get (d01zl)Option getting function
nag_ode_ivp_rkts_range (d02pe)Ordinary differential equations, initial value problem, Runge–Kutta method, integration over range with output
nag_ode_ivp_rkts_onestep (d02pf)Ordinary differential equations, initial value problem, Runge–Kutta method, integration over one step
nag_ode_ivp_rkts_setup (d02pq)Ordinary differential equations, initial value problem, setup for nag_ode_ivp_rkts_range (d02pe) and nag_ode_ivp_rkts_onestep (d02pf)
nag_ode_ivp_rkts_reset_tend (d02pr)Ordinary differential equations, initial value problem, resets end of range for nag_ode_ivp_rkts_onestep (d02pf)
nag_ode_ivp_rkts_interp (d02ps)Ordinary differential equations, initial value problem, interpolation for nag_ode_ivp_rkts_onestep (d02pf)
nag_ode_ivp_rkts_diag (d02pt)Ordinary differential equations, initial value problem, integration diagnostics for nag_ode_ivp_rkts_range (d02pe) and nag_ode_ivp_rkts_onestep (d02pf)
nag_ode_ivp_rkts_errass (d02pu)Ordinary differential equations, initial value problem, error assessment diagnostics for nag_ode_ivp_rkts_range (d02pe) and nag_ode_ivp_rkts_onestep (d02pf)
nag_interp_nd_scat_shep (e01zm)Interpolating function, modified Shepard's method, dd dimensions
nag_interp_nd_scat_shep_eval (e01zn)Interpolated values, evaluate interpolant computed by nag_interp_nd_scat_shep (e01zm), function and first derivatives, dd dimensions
nag_fit_1dspline_deriv_vector (e02bf)Evaluation of fitted cubic spline, function and optionally derivatives at a vector of points
nag_fit_2dspline_ts_sctr (e02jd)Spline approximation to a set of scattered data using a two-stage approximation method
nag_fit_2dspline_ts_evalv (e02je)Evaluation at a vector of points of a spline computed by nag_fit_2dspline_ts_sctr (e02jd)
nag_fit_2dspline_ts_evalm (e02jf)Evaluation at a mesh of points of a spline computed by nag_fit_2dspline_ts_sctr (e02jd)
nag_fit_opt_set (e02zk)Option setting routine
nag_fit_opt_get (e02zl)Option getting routine
nag_opt_miqp_mps_read (e04mx)Reads MPS data file defining LP, QP, MILP or MIQP problem
nag_bnd_lin_lsq (e04pc)Computes the least squares solution to a set of linear equations subject to fixed upper and lower bounds on the variables. An option is provided to return a minimal length solution if a solution is not unique
nag_matop_real_gen_matrix_log (f01ej)Real matrix logarithm
nag_matop_real_gen_matrix_fun_std (f01ek)Exponential, sine, cosine, sinh or cosh of a real matrix (Schur–Parlett algorithm)
nag_matop_real_gen_matrix_fun_num (f01el)Function of a real matrix (using numerical differentiation)
nag_matop_real_gen_matrix_fun_usd (f01em)Function of a real matrix (using user-supplied derivatives)
nag_matop_complex_gen_matrix_log (f01fj)Complex matrix logarithm
nag_matop_complex_gen_matrix_fun_std (f01fk)Exponential, sine, cosine, sinh or cosh of a complex matrix (Schur–Parlett algorithm)
nag_matop_complex_gen_matrix_fun_num (f01fl)Function of a complex matrix (using numerical differentiation)
nag_matop_complex_gen_matrix_fun_usd (f01fm)Function of a complex matrix (using user-supplied derivatives)
nag_matop_real_gen_matrix_actexp (f01ga)Action of a real matrix exponential on a real matrix
nag_matop_real_gen_matrix_actexp_rcomm (f01gb)Action of a real matrix exponential on a real matrix (reverse communication)
nag_matop_complex_gen_matrix_actexp (f01ha)Action of a complex matrix exponential on a complex matrix
nag_matop_complex_gen_matrix_actexp_rcomm (f01hb)Action of a complex matrix exponential on a complex matrix (reverse communication)
nag_matop_real_gen_matrix_cond_std (f01ja)Condition number for the exponential, logarithm, sine, cosine, sinh or cosh of a real matrix
nag_matop_real_gen_matrix_cond_num (f01jb)Condition number for a function of a real matrix (using numerical differentiation)
nag_matop_real_gen_matrix_cond_usd (f01jc)Condition number for a function of a real matrix (using user-supplied derivatives)
nag_matop_complex_gen_matrix_cond_std (f01ka)Condition number for the exponential, logarithm, sine, cosine, sinh or cosh of a complex matrix
nag_matop_complex_gen_matrix_cond_num (f01kb)Condition number for a function of a complex matrix (using numerical differentiation)
nag_matop_complex_gen_matrix_cond_usd (f01kc)Condition number for a function of a complex matrix (using user-supplied derivatives)
nag_eigen_real_gen_sparse_arnoldi (f02ek)Selected eigenvalues and eigenvectors of a real sparse general matrix
nag_linsys_real_gen_norm_rcomm (f04yd)Norm estimation (for use in condition estimation), real rectangular matrix
nag_linsys_complex_gen_norm_rcomm (f04zd)Norm estimation (for use in condition estimation), complex rectangular matrix
nag_sparse_real_gen_precon_bdilu (f11df)Real sparse nonsymmetric linear system, incomplete LULU factorization of local or overlapping diagonal blocks
nag_sparse_real_gen_solve_bdilu (f11dg)Solution of real sparse nonsymmetric linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, incomplete LULU block diagonal preconditioner computed by nag_sparse_real_gen_precon_bdilu (f11df)
nag_sparse_complex_gen_precon_bdilu (f11dt)Complex sparse nonsymmetric linear system, incomplete LULU factorization of local or overlapping diagonal blocks
nag_sparse_complex_gen_solve_bdilu (f11du)Solution of complex sparse nonsymmetric linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, incomplete LULU block diagonal preconditioner computed by nag_sparse_complex_gen_precon_bdilu (f11dt)
nag_sparseig_complex_band_init (f12at)Initialization function for (nag_sparseig_complex_band_solve (f12au)) computing selected eigenvalues and, optionally, eigenvectors of a complex banded (standard or generalized) eigenproblem.
nag_sparseig_complex_band_solve (f12au)Selected eigenvalues and, optionally, eigenvectors of complex non-Hermitian banded eigenproblem, driver
nag_blast_daxpby (f16ec)Real weighted vector addition
nag_blast_zaxpby (f16gc)Complex weighted vector addition
nag_stat_summary_onevar (g01at)Computes univariate summary information: mean, variance, skewness, kurtosis
nag_stat_summary_onevar_combine (g01au)Combines multiple sets of summary information, for use after nag_stat_summary_onevar (g01at)
nag_multi_students_t (g01hd)Computes the probability for the multivariate Student's tt-distribution
nag_stat_pdf_gamma_vector (g01kk)Computes a vector of values for the probability density function of the gamma distribution
nag_stat_pdf_normal_vector (g01kq)Computes a vector of values for the probability density function of the Normal distribution
nag_stat_pdf_multi_normal_vector (g01lb)Computes a vector of values for the probability density function of the multivariate Normal distribution
nag_stat_prob_normal_vector (g01sa)Computes a vector of probabilities for the standard Normal distribution
nag_stat_prob_students_t_vector (g01sb)Computes a vector of probabilities for the Student's tt-distribution
nag_stat_prob_chisq_vector (g01sc)Computes a vector of probabilities for χ2χ2 distribution
nag_stat_prob_f_vector (g01sd)Computes a vector of probabilities for FF-distribution
nag_stat_prob_beta_vector (g01se)Computes a vector of probabilities for the beta distribution
nag_stat_prob_gamma_vector (g01sf)Computes a vector of probabilities for the gamma distribution
nag_stat_prob_binomial_vector (g01sj)Computes a vector of probabilities for the binomial distribution
nag_stat_prob_poisson_vector (g01sk)Computes a vector of probabilities for the Poisson distribution
nag_stat_prob_hypergeom_vector (g01sl)Computes a vector of probabilities for the hypergeometric distribution
nag_stat_inv_cdf_normal_vector (g01ta)Computes a vector of deviates for the standard Normal distribution
nag_stat_inv_cdf_students_t_vector (g01tb)Computes a vector of deviates for Student's tt-distribution
nag_stat_inv_cdf_chisq_vector (g01tc)Computes a vector of deviates for χ2χ2 distribution
nag_stat_inv_cdf_f_vector (g01td)Computes a vector of deviates for FF-distribution
nag_stat_inv_cdf_beta_vector (g01te)Computes a vector of deviates for the beta distribution
nag_stat_inv_cdf_gamma_vector (g01tf)Computes a vector of deviates for the gamma distribution
nag_stat_moving_average (g01wa)Computes the mean and standard deviation using a rolling window
nag_nearest_correlation_h_weight (g02aj)Computes the nearest correlation matrix to a real square matrix, using element-wise weighting
nag_correg_ssqmat_combine (g02bz)Combines two sums of squares matrices, for use after nag_correg_ssqmat (g02bu)
nag_mv_gaussian_mixture (g03ga)Fits a Gaussian mixture model
nag_rand_bb_init (g05xa)Initializes the Brownian bridge generator
nag_rand_bb (g05xb)Generate paths for a free or non-free Wiener process using the Brownian bridge algorithm
nag_rand_bb_inc_init (g05xc)Initializes the generator which backs out the increments of sample paths generated by a Brownian bridge algorithm
nag_rand_bb_inc (g05xd)Backs out the increments from sample paths generated by a Brownian bridge algorithm
nag_rand_bb_make_bridge_order (g05xe)Creates a Brownian bridge construction order out of a set of input times
nag_rand_field_1d_user_setup (g05zm)Setup for simulating one-dimensional random fields, user-defined variogram
nag_rand_field_1d_predef_setup (g05zn)Setup for simulating one-dimensional random fields
nag_rand_field_1d_generate (g05zp)Generates realisations of a one-dimensional random field
nag_rand_field_2d_user_setup (g05zq)Setup for simulating two-dimensional random fields, user-defined variogram
nag_rand_field_2d_predef_setup (g05zr)Setup for simulating two-dimensional random fields, preset variogram
nag_rand_field_2d_generate (g05zs)Generates realisations of a two-dimensional random field
nag_rand_field_fracbm_generate (g05zt)Generates realisations of fractional Brownian motion
nag_tsa_inhom_iema (g13me)Computes the iterated exponential moving average for a univariate inhomogeneous time series
nag_tsa_inhom_iema_all (g13mf)Computes the iterated exponential moving average for a univariate inhomogeneous time series, intermediate results are also returned
nag_tsa_inhom_ma (g13mg)Computes the exponential moving average for a univariate inhomogeneous time series
nag_best_subset_given_size_revcomm (h05aa)Best nn subsets of size pp (reverse communication)
nag_best_subset_given_size (h05ab)Best nn subsets of size pp (direct communication)
nag_specfun_beta_log_real (s14cb)Logarithm of the beta function ln(B,a,b)ln(B,a,b)
nag_specfun_beta_incomplete (s14cc)Incomplete beta function Ix(a,b)Ix(a,b) and its complement 1Ix1-Ix
nag_specfun_bessel_y0_real_vector (s17aq)Bessel function vectorized Y0(x)Y0(x)
nag_specfun_bessel_y1_real_vector (s17ar)Bessel function vectorized Y1(x)Y1(x)
nag_specfun_bessel_j0_real_vector (s17as)Bessel function vectorized J0(x)J0(x)
nag_specfun_bessel_j1_real_vector (s17at)Bessel function vectorized J1(x)J1(x)
nag_specfun_airy_ai_real_vector (s17au)Airy function vectorized Ai(x)Ai(x)
nag_specfun_airy_bi_real_vector (s17av)Airy function vectorized Bi(x)Bi(x)
nag_specfun_airy_ai_deriv_vector (s17aw)Derivatives of the Airy function, vectorized Ai(x)Ai(x)
nag_specfun_airy_bi_deriv_vector (s17ax)Derivatives of the Airy function, vectorized Bi(x)Bi(x)
nag_specfun_bessel_k0_real_vector (s18aq)Modified Bessel function vectorized K0(x)K0(x)
nag_specfun_bessel_k1_real_vector (s18ar)Modified Bessel function vectorized K1(x)K1(x)
nag_specfun_bessel_i0_real_vector (s18as)Modified Bessel function vectorized I0(x)I0(x)
nag_specfun_bessel_i1_real_vector (s18at)Modified Bessel function vectorized I1(x)I1(x)
nag_specfun_bessel_k0_scaled_vector (s18cq)Scaled modified Bessel function vectorized exK0(x)exK0(x)
nag_specfun_bessel_k1_scaled_vector (s18cr)Scaled modified Bessel function vectorized exK1(x)exK1(x)
nag_specfun_bessel_i0_scaled_vector (s18cs)Scaled modified Bessel function vectorized e|x|I0(x)e-|x|I0(x)
nag_specfun_bessel_i1_scaled_vector (s18ct)Scaled modified Bessel function vectorized e|x|I1(x)e-|x|I1(x)
nag_specfun_kelvin_ber_vector (s19an)Kelvin function vectorized berxberx
nag_specfun_kelvin_bei_vector (s19ap)Kelvin function vectorized beixbeix
nag_specfun_kelvin_ker_vector (s19aq)Kelvin function vectorized kerxkerx
nag_specfun_kelvin_kei_vector (s19ar)Kelvin function vectorized keixkeix
nag_specfun_fresnel_s_vector (s20aq)Fresnel integral vectorized S(x)S(x)
nag_specfun_fresnel_c_vector (s20ar)Fresnel integral vectorized C(x)C(x)
nag_specfun_1f1_real (s22ba)Real confluent hypergeometric function 1F1 (a ; b ; x) F 1 1 (a;b;x)
nag_specfun_1f1_real_scaled (s22bb)Real confluent hypergeometric function 1F1 (a ; b ; x) F 1 1 (a;b;x)  in scaled form

NAG Toolbox

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