| Linear programming (LP), |
| dense, |
| active-set method/primal simplex, |
| alternative 1 | e04mfc |
| alternative 2 | e04ncc |
| sparse, |
| active-set method/primal simplex, |
| recommended (see Section 4.3 in the E04 Chapter Introduction) | e04nqc |
| alternative | e04nkc |
| Airy function, |
| , real argument, |
| scalar | s17agc |
| or , complex argument, optionally scaled | s17dgc |
| , real argument, |
| scalar | s17ajc |
| , real argument, |
| scalar | s17ahc |
| or , complex argument, optionally scaled | s17dhc |
| , real argument, |
| scalar | s17akc |
| Arccosh, |
| inverse hyperbolic cosine | s11acc |
| Arcsinh, |
| inverse hyperbolic sine | s11abc |
| Arctanh, |
| inverse hyperbolic tangent | s11aac |
| ARMA modelling, |
| ACF | g13abc |
| diagnostic checking | g13asc |
| differencing | g13aac |
| mean/range | g13auc |
| PACF | g13acc |
| Quadratic programming (QP), |
| dense, |
| active-set method for (possibly nonconvex) QP problem | e04nfc |
| active-set method for convex QP problem | e04ncc |
| sparse, |
| active-set method sparse convex QP problem, |
| recommended (see Section 4.3 in the E04 Chapter Introduction) | e04nqc |
| alternative | e04nkc |
| Bessel function, |
| , real argument, |
| scalar | s18aec |
| , real argument, |
| scalar | s18afc |
| , real argument, |
| scalar | s17aec |
| , real argument, |
| scalar | s17afc |
| , real argument, |
| scalar | s18acc |
| , real argument, |
| scalar | s18adc |
| , real argument, |
| scalar | s17acc |
| , real argument, |
| scalar | s17adc |
| Complement of the Cumulative Normal distribution, |
| scalar | s15acc |
| vectorized | s15aqc |
| Complement of the Error function, |
| real argument, |
| scalar | s15adc |
| vectorized | s15arc |
| real argument, scaled, |
| scalar | s15agc |
| vectorized | s15auc |
| Complex conjugate, |
| multiple Hermitian sequences | c06gqc |
| Complex sequence from Hermitian sequences | c06gsc |
| Compute error estimates, |
| real triangular matrix | f07thc |
| Cosine, |
| hyperbolic | s10acc |
| Cosine Integral | s13acc |
| Cumulative Normal distribution function, |
| scalar | s15abc |
| vectorized | s15apc |
| Nonlinear programming (NLP), |
| dense, |
| active-set sequential quadratic programming (SQP), |
| direct communication, |
| recommended (see Section 4.3 in the E04 Chapter Introduction) | e04ucc |
| alternative | e04wdc |
| reverse communication | e04ufc |
| sparse, |
| active-set sequential quadratic programming (SQP), |
| alternative | e04vhc |
| alternative | e04ugc |
| Dawson's Integral, |
| scalar | s15afc |
| vectorized | s15atc |
| Derivative, |
| of interpolant, |
| from e01bec | e01bgc |
| Descriptive statistics / Exploratory analysis, |
| summaries, |
| frequency / contingency table, |
| one variable | g01aec |
| mean, variance, skewness, kurtosis (one variable), |
| from frequency table | g01adc |
| median, hinges / quartiles, minimum, maximum | g01alc |
| quantiles, |
| unordered vector |
| unweighted | g01amc |
| Digamma function, scaled | s14adc |
| Discrete Fourier Transform, |
| one-dimensional, |
| multiple transforms, |
| Hermitian sequence, |
| real storage by rows | c06fqc |
| real sequence, |
| real storage by rows | c06fpc |
| Distributions, |
| Beta, |
| central, |
| deviates, |
| scalar | g01fec |
| probabilities and probability density function, |
| scalar | g01eec |
| non-central, |
| probabilities | g01gec |
| binomial, |
| distribution function, |
| scalar | g01bjc |
| Durbin–Watson statistic, |
| probabilities | g01epc |
| energy loss distributions, |
| Landau, |
| density | g01mtc |
| derivative of density | g01rtc |
| distribution | g01etc |
| first moment | g01ptc |
| inverse distribution | g01ftc |
| second moment | g01qtc |
| Vavilov, |
| density | g01muc |
| distribution | g01euc |
| initialization | g01zuc |
| : |
| central, |
| deviates, |
| scalar | g01fdc |
| probabilities, |
| scalar | g01edc |
| non-central, |
| probabilities | g01gdc |
| gamma, |
| deviates, |
| scalar | g01ffc |
| probabilities, |
| scalar | g01efc |
| Hypergeometric, |
| distribution function, |
| scalar | g01blc |
| Kolomogorov–Smirnov, |
| probabilities, |
| one-sample | g01eyc |
| two-sample | g01ezc |
| Normal, |
| bivariate, |
| probabilities | g01hac |
| multivariate, |
| probabilities | g01hbc |
| quadratic forms, |
| cumulants and moments | g01nac |
| moments of ratios | g01nbc |
| univariate, |
| deviates, |
| scalar | g01fac |
| probabilities, |
| scalar | g01eac |
| reciprocal of Mill's Ratio | g01mbc |
| Shapiro and Wilk's test for Normality | g01ddc |
| Poisson, |
| distribution function, |
| scalar | g01bkc |
| Student's : |
| central, |
| univariate, |
| deviates, |
| scalar | g01fbc |
| probabilities, |
| scalar | g01ebc |
| non-central, |
| probabilities | g01gbc |
| Studentized range statistic, |
| deviates | g01fmc |
| probabilities | g01emc |
| von Mises, |
| probabilities | g01erc |
| : |
| central, |
| deviates | g01fcc |
| probabilities | g01ecc |
| probability of linear combination | g01jdc |
| non-central, |
| probabilities | g01gcc |
| probability of linear combination | g01jcc |
| Nonlinear programming (NLP) – derivative-free optimization (DFO), |
| model-based method for bound-constrained optimization | e04jcc |
| model-based method for bound-constrained optimization, |
| reverse communication | e04jec |
| direct communication | e04jdc |
| Nelder–Mead simplex method for unconstrained optimization | e04cbc |
| Eigenvalue problems for condensed forms of matrices, |
| complex Hermitian matrix, |
| eigenvalues and eigenvectors, |
| general matrix, |
| all/selected eigenvalues and eigenvectors by root-free algorithm | f08fpc |
| all eigenvalues and eigenvectors by a divide-and-conquer algorithm | f08fqc |
| eigenvalues only, |
| general matrix, |
| all/selected eigenvalues by the Pal–Walker–Kahan variant of the or algorithm | f08fpc |
| real symmetric matrix, |
| eigenvalues and eigenvectors, |
| general matrix, |
| all/selected eigenvalues and eigenvectors by root-free algorithm | f08fbc |
| all eigenvalues and eigenvectors by a divide-and-conquer algorithm | f08fcc |
| all eigenvalues and eigenvectors by root-free algorithm | f08fac |
| eigenvalues only, |
| general matrix, |
| all/selected eigenvalues by the Pal–Walker–Kahan variant of the or algorithm | f08fbc |
| all eigenvalues by the Pal–Walker–Kahan variant of the or algorithm | f08fac |
| Eigenvalue problems for nonsymmetric matrices, |
| complex matrix, |
| all eigenvalues and left/right eigenvectors, plus balancing transformation and reciprocal condition numbers | f08npc |
| real matrix, |
| all eigenvalues and left/right eigenvectors, plus balancing transformation and reciprocal condition numbers | f08nbc |
| Elliptic functions, Jacobian, sn, cn, dn, |
| complex argument | s21cbc |
| real argument | s21cac |
| Elliptic integral, |
| Legendre form, |
| complete of 1st kind, | s21bhc |
| complete of 2nd kind, | s21bjc |
| of 1st kind, | s21bec |
| of 2nd kind, | s21bfc |
| of 3rd kind, | s21bgc |
| symmetrised, |
| degenerate of 1st kind, | s21bac |
| of 1st kind, | s21bbc |
| of 2nd kind, | s21bcc |
| of 3rd kind, | s21bdc |
| Erf, |
| real argument, |
| scalar | s15aec |
| vectorized | s15asc |
| Erfc, |
| real argument, |
| scalar | s15adc |
| vectorized | s15arc |
| erfcx, |
| real argument, |
| scalar | s15agc |
| vectorized | s15auc |
| Evaluation, |
| at a point, |
| of cubic splines | e02bbc |
| of cubic splines and derivatives | e02bcc |
| at vector of points, |
| of bicubic splines at vector of points | e02dec |
| of interpolant, |
| from e01bec | e01bfc |
| from triangulation from e01eac | e01ebc |
| on mesh, |
| of bicubic splines | e02dfc |
| Exponential Integral | s13aac |
| Exponential smoothing | g13amc |
| Extrapolation, |
| one variable, |
| piecewise cubic | e01bec |
| polynomial, |
| general data | e01aac |
| Nonlinear programming (NLP) – special cases, |
| unidimensional optimization (one-dimensional) with bound constraints, |
| method based on quadratic interpolation, no derivatives | e04abc |
| method based on cubic interpolation | e04bbc |
| unconstrained, |
| preconditioned conjugate gradient method | e04dgc |
| bound-constrained, |
| modified Newton algorithm, first and second derivatives | e04lbc |
| Fresnel integral, |
| , |
| scalar | s20adc |
| , |
| scalar | s20acc |
| Nonlinear programming (NLP) – global optimization, |
| bound constrained, |
| branching algorithm, multi-level coordinate search | e05kbc |
| branching algorithm, multi-level coordinate search (D) | e05jbc |
| generic, including nonlinearly constrained, |
| multi-start | e05ucc |
| Gamma function, |
| incomplete, |
| scalar | s14bac |
| vectorized | s14bnc |
| scalar | s14aac |
| vectorized | s14anc |
| GARCH, |
| GJR GARCH, |
| fitting | g13fec |
| forecasting | g13ffc |
| symmetric or type I AGARCH, |
| fitting | g13fac |
| forecasting | g13fbc |
| type II AGARCH, |
| fitting | g13fcc |
| forecasting | g13fdc |
| Generalized eigenvalue problems for nonsymmetric matrix pairs, |
| complex nonsymmetric matrix pairs, |
| all eigenvalues and left/right eigenvectors, plus the balancing transformation and reciprocal condition numbers | f08wpc |
| real nonsymmetric matrix pairs, |
| all eigenvalues and left/right eigenvectors, plus the balancing transformation and reciprocal condition numbers | f08wbc |
| Generalized factorial function, |
| scalar | s14aac |
| vectorized | s14anc |
| Generalized linear models, |
| binomial errors | g02gbc |
| computes estimable function | g02gnc |
| gamma errors | g02gdc |
| Normal errors | g02gac |
| Poisson errors | g02gcc |
| prediction | g02gpc |
| transform model parameters | g02gkc |
| Generating samples, matrices and tables, |
| random correlation matrix | g05pyc |
| random orthogonal matrix | g05pxc |
| random permutation of an integer vector | g05ncc |
| random sample from an integer vector, |
| unequal weights, without replacement | g05nec |
| unweighted, without replacement | g05ndc |
| random table | g05pzc |
| resample from an integer vector, |
| unequal weights | g05nfc |
| Generation of time series, |
| asymmetric GARCH Type II | g05pec |
| asymmetric GJR GARCH | g05pfc |
| EGARCH | g05pgc |
| exponential smoothing | g05pmc |
| type I AGARCH | g05pdc |
| univariate ARMA | g05phc |
| vector ARMA | g05pjc |
| Linear least squares, linear regression, data fitting, |
| constrained, |
| bound-constrained least squares problem | e04pcc |
| linearly-constrained active-set method | e04ncc |
| Data fitting, |
| general loss functions (for sum of squares, see nonlinear least squares) | e04gnc |
| Nonlinear least squares, data fitting, |
| unconstrained, |
| combined Gauss–Newton and modified Newton algorithm, |
| no derivatives | e04fcc |
| combined Gauss–Newton and quasi-Newton algorithm, |
| first derivatives | e04gbc |
| bound constrained, |
| model-based derivative-free algorithm, |
| direct communication | e04ffc |
| reverse communication | e04fgc |
| trust region algorithm, |
| first derivatives, optionally second derivatives | e04ggc |
| Nonlinear least squares, data fitting – global optimization, |
| generic, including nonlinearly constrained, |
| multi-start | e05usc |
| Mixed integer linear programming (MILP), |
| dense, |
| branch and bound method | h02bbc |
| Integration (definite) of interpolant from e01bec | e01bhc |
| Interpolated values, |
| one variable, |
| from interpolant from e01bec | e01bfc |
| from interpolant from e01bec (including derivative) | e01bgc |
| from polynomial, |
| general data | e01aac |
| two variables, |
| barycentric, from triangulation from e01eac | e01ebc |
| Interpolating function, |
| one variable, |
| cubic spline | e01bac |
| other piecewise polynomial | e01bec |
| two variables, |
| bicubic spline | e01dac |
| NAG optimization modelling suite, |
| solvers, |
| constrained nonlinear data fitting (NLDF) | e04gnc |
| derivative-free optimisation (DFO) for nonlinear least squares problems, |
| direct communication | e04ffc |
| reverse communication | e04fgc |
| trust region optimisation for nonlinear least squares problems (BXNL) | e04ggc |
| model-based method for bound-constrained optimization, |
| direct communication | e04jdc |
| reverse communication | e04jec |
| Jacobian theta functions , |
| real argument | s21ccc |
| Service functions, |
| derivative check and approximation, |
| check user's function for calculating first derivatives of function | e04hcc |
| check user's function for calculating second derivatives of function | e04hdc |
| check user's function for calculating Jacobian of first derivatives | e04yac |
| estimate (using numerical differentiation) gradient and/or Hessian of a function | e04xac |
| determine the pattern of nonzeros in the Jacobian matrix for e04vhc | e04vjc |
| Kelvin function, |
| , |
| scalar | s19abc |
| , |
| scalar | s19aac |
| , |
| scalar | s19adc |
| , |
| scalar | s19acc |
| Korobov optimal coefficients for use in d01gdc: |
| when number of points is a product of primes | d01gzc |
| when number of points is prime | d01gyc |
| least squares problems, |
| real matrices, |
| minimum norm solution using a complete orthogonal factorization | f08bac |
| minimum norm solution using the singular value decomposition (divide-and-conquer) | f08kcc |
| Least squares surface fit, |
| with bicubic splines | e02dac |
| Legendre functions of 1st kind , | s22aac |
| Linear mixed effects regression, |
| via maximum likelihood (ML) | g02jbc |
| via restricted maximum likelihood (REML) | g02jac |
| or factorization, |
| real symmetric positive definite band matrix | f07hdc |
| real symmetric positive definite matrix | f07fdc |
| Logarithm of | s01bac |
| Logarithm of gamma function, |
| real, |
| scalar | s14abc |
| vectorized | s14apc |
| factorization, |
| complex matrix | f07arc |
| real matrix | f07adc |
| real tridiagonal matrix | f07cdc |
| Matrix Arithmetic and Manipulation, |
| matrix storage conversion, |
| full to packed triangular storage, |
| complex matrices | f01vbc |
| real matrices | f01vac |
| full to Rectangular Full Packed storage, |
| complex matrix | f01vfc |
| real matrix | f01vec |
| packed triangular to full storage, |
| complex matrices | f01vdc |
| real matrices | f01vcc |
| packed triangular to Rectangular Full Packed storage, |
| complex matrices | f01vkc |
| real matrices | f01vjc |
| Rectangular Full Packed to full storage, |
| complex matrices | f01vhc |
| real matrices | f01vgc |
| Rectangular Full Packed to packed triangular storage, |
| complex matrices | f01vmc |
| real matrices | f01vlc |
| Matrix function, |
| complex Hermitian matrix, |
| matrix exponential | f01fdc |
| matrix function | f01ffc |
| complex matrix, |
| matrix exponential | f01fcc |
| real symmetric matrix, |
| matrix exponential | f01edc |
| matrix function | f01efc |
| Matrix inversion, |
| after factorizing the matrix of coefficients, |
| real matrix | f07ajc |
| real symmetric positive definite matrix | f07fjc |
| real triangular matrix | f07tjc |
| Multidimensional quadrature, |
| over a finite two-dimensional region | d01dac |
| over a general product region, |
| Korobov–Conroy number-theoretic method | d01gdc |
| over a hyper-rectangle, |
| Gaussian quadrature rule-evaluation | d01fbc |
| over an -simplex | d01pac |
| Multiple linear regression/General linear model, |
| add/delete observation from model | g02dcc |
| add independent variable to model | g02dec |
| computes estimable function | g02dnc |
| delete independent variable from model | g02dfc |
| general linear regression model | g02dac |
| regression for new dependent variable | g02dgc |
| regression parameters from updated model | g02ddc |
| transform model parameters | g02dkc |
| Nearest correlation matrix, |
| -factor structure | g02aec |
| method of Qi and Sun, |
| unweighted, unbounded | g02aac |
| weighted norm | g02abc |
| Non-parametric rank correlation (Kendall and/or Spearman): |
| missing values, |
| casewise treatment of missing values, |
| preserving input data | g02brc |
| One-dimensional quadrature, |
| adaptive integration of a function over a finite interval, |
| strategy due to Gonnet, |
| suitable for badly behaved integrals, |
| vectorized interface | d01rgc |
| strategy due to Piessens and de Doncker, |
| allowing for singularities at user-specified break-points | d01rlc |
| suitable for badly behaved integrands | d01rjc |
| suitable for highly oscillatory integrals | d01rkc |
| integration of a function defined by data values only, |
| Gill–Miller method | d01gac |
| non-adaptive integration over a finite interval | d01bdc |
| Operations on eigenvectors of a real symmetric or complex Hermitian matrix, or singular vectors of a general matrix, |
| estimate condition numbers | f08flc |
| Option Pricing, |
| American option, Bjerksund and Stensland option price | s30qcc |
| Asian option, geometric continuous average rate price | s30sac |
| Asian option, geometric continuous average rate price with Greeks | s30sbc |
| binary asset-or-nothing option price | s30ccc |
| binary asset-or-nothing option price with Greeks | s30cdc |
| binary cash-or-nothing option price | s30cac |
| binary cash-or-nothing option price with Greeks | s30cbc |
| Black–Scholes implied volatility | s30acc |
| Black–Scholes–Merton option price | s30aac |
| Black–Scholes–Merton option price with Greeks | s30abc |
| European option, option prices, using Merton jump-diffusion model | s30jac |
| European option, option price with Greeks, using Merton jump-diffusion model | s30jbc |
| floating-strike lookback option price | s30bac |
| floating-strike lookback option price with Greeks | s30bbc |
| Heston's model option price | s30nac |
| Heston's model option price with Greeks | s30nbc |
| Heston's model option price with Greeks, sensitivities of model parameters and negative rates | s30ndc |
| Heston's model with term structure | s30ncc |
| standard barrier option price | s30fac |
| Outlier detection, |
| Peirce, |
| raw data or single variance supplied | g07gac |
| two variances supplied | g07gbc |
| Overdetermined and underdetermined linear systems, |
| complex matrices, |
| solves an overdetermined or undetermined complex linear system | f08anc |
| real matrices, |
| solves an overdetermined or undetermined real linear system | f08aac |
| Partial least squares, |
| calculates predictions given an estimated PLS model | g02ldc |
| fits a PLS model for a given number of factors | g02lcc |
| orthogonal scores using SVD | g02lac |
| orthogonal scores using Wold's method | g02lbc |
| Polygamma function, |
| , real | s14aec |
| Principal component analysis | g03aac |
| Product-moment correlation, |
| correlation matrix, |
| compute correlation and covariance matrices | g02bxc |
| compute from sum of squares matrix | g02bwc |
| compute partial correlation and covariance matrices | g02byc |
| sum of squares matrix, |
| compute | g02buc |
| update | g02btc |
| Pseudorandom numbers, |
| array of variates from multivariate distributions, |
| Dirichlet distribution | g05sec |
| multinomial distribution | g05tgc |
| Normal distribution | g05rzc |
| Student's distribution | g05ryc |
| copulas, |
| Gaussian copula | g05rdc |
| Student's copula | g05rcc |
| initialize generator, |
| multiple streams, |
| leap-frog | g05khc |
| skip-ahead | g05kjc |
| skip-ahead (power of 2) | g05kkc |
| vector of variates from discrete univariate distributions, |
| binomial distribution | g05tac |
| geometric distribution | g05tcc |
| hypergeometric distribution | g05tec |
| logarithmic distribution | g05tfc |
| logical value Nag_TRUE or Nag_FALSE | g05tbc |
| negative binomial distribution | g05thc |
| Poisson distribution | g05tjc |
| uniform distribution | g05tlc |
| user-supplied distribution | g05tdc |
| variate array from discrete distributions with array of parameters, |
| Poisson distribution with varying mean | g05tkc |
| vectors of variates from continuous univariate distributions, |
| beta distribution | g05sbc |
| Cauchy distribution | g05scc |
| exponential mix distribution | g05sgc |
| -distribution | g05shc |
| gamma distribution | g05sjc |
| logistic distribution | g05slc |
| log-normal distribution | g05smc |
| negative exponential distribution | g05sfc |
| Normal distribution | g05skc |
| real number from the continuous uniform distribution | g05sac |
| Student's -distribution | g05snc |
| triangular distribution | g05spc |
| uniform distribution | g05sqc |
| von Mises distribution | g05src |
| Weibull distribution | g05ssc |
| square distribution | g05sdc |
| psi function | s14acc |
| psi function derivatives, scaled | s14adc |
| factorization and related operations, |
| real matrices, |
| general matrices, |
| apply orthogonal matrix | f08agc |
| factorization, |
| with column pivoting, using BLAS-3 | f08bfc |
| factorization, orthogonal matrix | f08aec |
| factorization, with column pivoting, deprecated | f08bec |
| Quantile regression, |
| linear, |
| comprehensive | g02qgc |
| simple | g02qfc |
| Quasi-random numbers, |
| array of variates from univariate distributions, |
| uniform distribution | g05ymc |
| initialize generator, |
| scrambled Sobol or Niederreiter | g05ync |
| Sobol, Niederreiter or Faure | g05ylc |
| Residuals, |
| Durbin–Watson test | g02fcc |
| standardized residuals and influence statistics | g02fac |
| Ridge regression, |
| ridge parameter(s) supplied | g02kbc |
| ridge parameter optimized | g02kac |
| Robust correlation, |
| Huber's method | g02hkc |
| user-supplied weight function only | g02hmc |
| user-supplied weight function plus derivatives | g02hlc |
| Robust regression, |
| compute weights for use with g02hdc | g02hbc |
| standard -estimates | g02hac |
| user-supplied weight functions | g02hdc |
| variance-covariance matrix following g02hdc | g02hfc |
| Scaled modified Bessel function(s), |
| , real argument, |
| scalar | s18cec |
| , real argument, |
| scalar | s18cfc |
| , real argument, |
| scalar | s18ccc |
| , real argument, |
| scalar | s18cdc |
| Scores, |
| Normal scores, |
| accurate | g01dac |
| variance-covariance matrix | g01dcc |
| Normal scores, ranks or exponential (Savage) scores | g01dhc |
| Simple linear regression, |
| no intercept | g02cbc |
| with intercept | g02cac |
| Sine, |
| hyperbolic | s10abc |
| Sine Integral | s13adc |
| Singular value decomposition, |
| complex matrix, |
| using bidiagonal iteration | f08kpc |
| real matrix, |
| using a divide-and-conquer algorithm | f08kdc |
| using bidiagonal iteration | f08kbc |
| Solution of simultaneous linear equations, |
| after factorizing the matrix of coefficients, |
| complex matrix | f07asc |
| real symmetric positive definite band matrix | f07hec |
| real symmetric positive definite matrix | f07fec |
| real tridiagonal matrix | f07cec |
| expert drivers (with condition and error estimation): |
| complex Hermitian positive definite matrix | f07fpc |
| complex matrix | f07apc |
| real matrix | f07abc |
| real symmetric positive definite matrix | f07fbc |
| simple drivers, |
| real matrix | f07aac |
| real symmetric positive definite matrix | f07fac |
| real triangular matrix | f07tec |
| real tridiagonal matrix | f07cac |
| Spectral analysis |
| Bivariate, |
| Bartlett, Tukey, Parzen windows | g13ccc |
| cross amplitude spectrum | g13cec |
| direct smoothing | g13cdc |
| gain and phase | g13cfc |
| noise spectrum | g13cgc |
| Univariate, |
| Bartlett, Tukey, Parzen windows | g13cac |
| direct smoothing | g13cbc |
| Stepwise linear regression, |
| Clarke's sweep algorithm | g02efc |
| Tangent, |
| hyperbolic | s10aac |
| Transfer function modelling, |
| cross-correlations | g13bcc |
| filtering | g13bbc |
| fitting | g13bec |
| forecasting from fully specified model | g13bjc |
| preliminary estimation | g13bdc |
| pre-whitening | g13bac |
| update state set | g13bgc |
| Trigamma function, scaled | s14adc |
| Vector ARMA, |
| differencing | g13dlc |
| fitting | g13ddc |
| forecasting | g13djc |
| update forecast | g13dkc |
| zeros of ARIMA operator | g13dxc |
| Weights and abscissae for Gaussian quadrature rules, |
| more general choice of rule, |
| calculating the weights and abscissae | d01tcc |
| Zeros of Bessel functions , , , , |
| scalar | s17alc |
| Zeros of functions of one variable, |
| direct communication, |
| binary search followed by Brent algorithm | c05auc |
| Brent algorithm | c05ayc |
| continuation method | c05awc |
| reverse communication, |
| binary search | c05avc |
| Brent algorithm | c05azc |
| continuation method | c05axc |
| Zeros of functions of several variables, |
| checking function, |
| checks user-supplied Jacobian | c05zdc |
| direct communication, |
| easy-to-use, |
| derivatives required | c05rbc |
| no derivatives required | c05qbc |
| sophisticated, |
| derivatives required | c05rcc |
| no derivatives required | c05qcc |
| reverse communication, |
| sophisticated, |
| derivatives required | c05rdc |
| no derivatives required | c05qdc |