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, semi-infinite or infinite interval, |
using pre-computed weights and abscissae |
single abscissae interface | d01tac |
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 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 |