function nag_con

% NAG_CON Show the help for the functions in this toolbox.

% This file is automatically generated.  Matthew Simoneau, 09-04-98
% Copyright (c) 1984-98 by The MathWorks, Inc. All Rights Reserved
% $Revision: 1.5 $ $Date: 1998/10/16 23:19:26 $

helpwin('nag_con/Contents');

function Contents
%MATLAB Tour Partial Function Help:  nag_con
%
%Double click on any function for more information
%
%  NAG Foundation Toolbox - Numerical & Statistical Library
%  Version 1.0.3 (R11)  21-Nov-1997
% 
%  C02 -- Zeros of Polynomials
% 
%  C02AFF  All zeros of complex polynomial, modified Laguerre method
% 
%  C02AGF  All zeros of real polynomial, modified Laguerre method
% 
% 
% 
%  C05 -- Roots of One or More Transcendental Equations
% 
%  C05ADF  Zero of continuous function in given interval, Bus and Dekker
%  algorithm
% 
%  C05NBF  Solution of system of nonlinear equations using function values
%  only (easy-to-use)
% 
%  C05PBF  Solution of system of nonlinear equations using 1st derivatives
%  (easy-to-use)
% 
%  C05ZAF  Check user's routine for calculating 1st derivatives
% 
% 
% 
%  C06 -- Summation of Series
% 
%  C06EAF  Single 1-D real discrete Fourier transform, no extra workspace
% 
%  C06EBF  Single 1-D Hermitian discrete Fourier transform, no extra workspace
% 
%  C06ECF  Single 1-D complex discrete Fourier transform, no extra workspace
% 
%  C06EKF  Circular convolution or correlation of two real vectors, no extra
%  workspace
% 
%  C06FPF  Multiple 1-D real discrete Fourier transforms
% 
%  C06FQF  Multiple 1-D Hermitian discrete Fourier transforms
% 
%  C06FRF  Multiple 1-D complex discrete Fourier transforms
% 
%  C06FUF  2-D complex discrete Fourier transform
% 
%  C06GBF  Complex conjugate of Hermitian sequence
% 
%  C06GQF  Complex conjugate of multiple Hermitian sequences
% 
%  C06GSF  Convert Hermitian sequences to general complex sequences
% 
% 
% 
%  D01 -- Quadrature
% 
%  D01AJF  1-D quadrature, adaptive, finite interval, strategy due to Piessens
%  and de Doncker, allowing for badly-behaved integrands
% 
%  D01AKF  1-D quadrature, adaptive, finite interval, method suitable for
%  oscillating functions
% 
%  D01ALF  1-D quadrature, adaptive, finite interval, allowing for singularities
%  at user-specified break-points
% 
%  D01AMF  1-D quadrature, adaptive, infinite or semi-infinite interval
% 
%  D01ANF  1-D quadrature, adaptive, finite interval, weight function
%  cos ( omega x) or sin ( omega x)
% 
%  D01APF  1-D quadrature, adaptive, finite interval, weight function with
%  end-point singularities of algebraico-logarithmic type
% 
%  D01AQF  1-D quadrature, adaptive, finite interval, weight function 1/(x - c),
%  Cauchy principal value (Hilbert transform)
% 
%  D01ASF  1-D quadrature, adaptive, semi-infinite interval, weight function
%  cos ( omega x) or sin ( omega x)
% 
%  D01BBF  Pre-computed weights and abscissae for Gaussian quadrature rules,
%  restricted choice of rule
% 
%  D01FCF  Multi-dimensional adaptive quadrature over hyper-rectangle
% 
%  D01GAF  1-D quadrature, integration of function defined by data values,
%  Gill-Miller method
% 
%  D01GBF  Multi-dimensional quadrature over hyper-rectangle, Monte Carlo
%  method
% 
% 
% 
%  D02 -- Ordinary Differential Equations
% 
%  D02BBF  ODEs, IVP, Runge-Kutta-Merson method, over a range, intermediate
%  output (simple driver)
% 
%  D02BHF  ODEs, IVP, Runge-Kutta-Merson method, until function of solution
%  is zero (simple driver)
% 
%  D02CJF  ODEs, IVP, Adams method, until function of solution is zero,
%  intermediate output (simple driver)
% 
%  D02EJF  ODEs, stiff IVP, BDF method, until function of solution is zero,
%  intermediate output (simple driver)
% 
%  D02GAF  ODEs, boundary value problem, finite difference technique with
%  deferred correction, simple nonlinear problem
% 
%  D02GBF  ODEs, boundary value problem, finite difference technique with
%  deferred correction, general linear problem
% 
%  D02KEF  2nd order Sturm-Liouville problem, regular/singular system,
%  finite/infinite range, eigenvalue and eigenfunction, user-specified
%  break-points
% 
%  D02RAF  ODEs, general nonlinear boundary value problem, finite difference
%  technique with deferred correction, continuation facility
% 
% 
% 
%  D03 -- Partial Differential Equations
% 
%  D03EDF  Elliptic PDE, solution of finite difference equations by a
%  multigrid technique
% 
%  D03EEF  Discretize a 2nd order elliptic PDE on a rectangle
% 
% 
% 
%  E01 -- Interpolation
% 
%  E01BAF  Interpolating functions, cubic spline interpolant, one variable
% 
%  E01BEF  Interpolating functions, monotonicity-preserving, piecewise cubic
%  Hermite, one variable
% 
%  E01BFF  Interpolated values, interpolant computed by E01BEF, function only,
%  one variable
% 
%  E01BGF  Interpolated values, interpolant computed by E01BEF, function and
%  1st derivative, one variable
% 
%  E01BHF  Interpolated values, interpolant computed by E01BEF, definite
%  integral, one variable
% 
%  E01DAF  Interpolating functions, fitting bicubic spline, data on rectangular
%  grid
% 
%  E01SAF  Interpolating functions, method of Renka and Cline, two variables
% 
%  E01SBF  Interpolated values, evaluate interpolant computed by E01SAF, two
%  variables
% 
%  E01SEF  Interpolating functions, modified Shepard's method, two variables
% 
%  E01SFF  Interpolated values, evaluate interpolant computed by E01SEF, two
%  variables
% 
% 
% 
%  E02 -- Curve and Surface Fitting
% 
%  E02ADF  Least-squares curve fit, by polynomials, arbitrary data points
% 
%  E02AEF  Evaluation of fitted polynomial in one variable from Chebyshev
%  series form (simplified parameter list)
% 
%  E02AGF  Least-squares polynomial fit, values and derivatives may be
%  constrained, arbitrary data points,
% 
%  E02AHF  Derivative of fitted polynomial in Chebyshev series form
% 
%  E02AJF  Integral of fitted polynomial in Chebyshev series form
% 
%  E02AKF  Evaluation of fitted polynomial in one variable, from Chebyshev
%  series form
% 
%  E02BAF  Least-squares curve cubic spline fit (including interpolation)
% 
%  E02BBF  Evaluation of fitted cubic spline, function only
% 
%  E02BCF  Evaluation of fitted cubic spline, function and derivatives
% 
%  E02BDF  Evaluation of fitted cubic spline, definite integral
% 
%  E02BEF  Least-squares cubic spline curve fit, automatic knot placement
% 
%  E02DAF  Least-squares surface fit, bicubic splines
% 
%  E02DCF  Least-squares surface fit by bicubic splines with automatic knot
%  placement, data on rectangular grid
% 
%  E02DDF  Least-squares surface fit by bicubic splines with automatic knot
%  placement, scattered data
% 
%  E02DEF  Evaluation of a fitted bicubic spline at a vector of points
% 
%  E02DFF  Evaluation of a fitted bicubic spline at a mesh of points
% 
%  E02GAF  L -approximation by general linear function
%           1
%  E02ZAF  Sort 2-D data into panels for fitting bicubic splines
% 
% 
% 
%  E04 -- Minimizing or Maximizing a Function
% 
%  E04DGF  Unconstrained minimum, pre-conditioned conjugate gradient
%  algorithm, function of several variables using 1st derivatives
%  (comprehensive)
% 
%  E04DKF  Supply optional parameter values to E04DGF
% 
%  E04FDF  Unconstrained minimum of a sum of squares, combined Gauss-Newton
%  and modified Newton algorithm using function values only (easy-to-use)
% 
%  E04GCF  Unconstrained minimum of a sum of squares, combined Gauss-Newton
%  and quasi-Newton algorithm, using 1st derivatives (easy-to-use)
% 
%  E04JAF  Minimum, function of several variables, quasi-Newton algorithm,
%  simple bounds, using function values only (easy-to-use)
% 
%  E04MBF  Linear programming problem (easy-to-use)
% 
%  E04NAF  Quadratic programming problem (comprehensive)
% 
%  E04UCF  Minimum, function of several variables, sequential QP method,
%  nonlinear constraints, using function values and optionally 1st
%  derivatives (comprehensive)
% 
%  E04UEF  Supply optional parameter values to E04UCF
% 
%  E04YCF  Covariance matrix for nonlinear least-squares problem
% 
% 
% 
%  F01 -- Matrix Factorizations
% 
%  F01BRF  LU factorization of real sparse matrix
% 
%  F01BSF  LU factorization of real sparse matrix with known sparsity pattern
% 
%  F01MAF  Incomplete Cholesky factorization of real sparse symmetric
%  positive-definite matrix
% 
%             T
%  F01MCF  LDL  factorization of real symmetric positive-definite
%  variable-bandwidth matrix
% 
%  F01QCF  QR factorization of real m by n matrix (m >= n)
% 
%                                                              T
%  F01QDF  Operations with orthogonal matrices, compute QB or Q B after
%  factorization by F01QCF or F01QFF
% 
%  F01QEF  Operations with orthogonal matrices, form columns of Q after
%  factorization by F01QCF or F01QFF
% 
%  F01RCF  QR factorization of complex m by n matrix (m >= n)
% 
%                                                           H
%  F01RDF  Operations with unitary matrices, compute QB or Q B after
%  factorization by F01RCF
% 
%  F01REF  Operations with unitary matrices, form columns of Q after
%  factorization by F01RCF
% 
% 
% 
%  F02 -- Eigenvalue and Eigenvectors
% 
%  F02AAF  All eigenvalues of real symmetric matrix (Black Box)
% 
%  F02ABF  All eigenvalues and eigenvectors of real symmetric matrix
%  (Black Box)
% 
%  F02ADF  All eigenvalues of generalized real symmetric-definite
%  eigenproblem (Black Box)
% 
%  F02AEF  All eigenvalues and eigenvectors of generalized real
%  symmetric-definite eigenproblem (Black Box)
% 
%  F02AFF  All eigenvalues of real matrix (Black Box)
% 
%  F02AGF  All eigenvalues and eigenvectors of real matrix (Black Box)
% 
%  F02AJF  All eigenvalues of complex matrix (Black Box)
% 
%  F02AKF  All eigenvalues and eigenvectors of complex matrix (Black Box)
% 
%  F02AWF  All eigenvalues of complex Hermitian matrix (Black Box)
% 
%  F02AXF  All eigenvalues and eigenvectors of complex Hermitian matrix
%  (Black Box)
% 
%  F02BBF  Selected eigenvalues and eigenvectors of real symmetric matrix
%  (Black Box)
% 
%  F02BJF  All eigenvalues and optionally eigenvectors of generalized
%  eigenproblem by QZ algorithm, real matrices (Black Box)
% 
%  F02FJF  Selected eigenvalues and eigenvectors of sparse symmetric
%  eigenproblem (Black Box)
% 
%  F02WEF  SVD of real matrix
% 
%  F02XEF  SVD of complex matrix
% 
% 
% 
%  F04 -- Simultaneous Linear Equations
% 
%  F04ADF  Approximate solution of complex simultaneous linear equations
%  with multiple right-hand sides (Black Box)
% 
%  F04ARF  Approximate solution of real simultaneous linear equations, one
%  right-hand side (Black Box)
% 
%  F04ASF  Accurate solution of real symmetric positive-definite simultaneous
%  linear equations, one right-hand side (Black Box)
% 
%  F04ATF  Accurate solution of real simultaneous linear equations, one
%  right-hand side (Black Box)
% 
%  F04AXF  Approximate solution of real sparse simultaneous linear equations
%  (coefficient matrix already factorized)
% 
%  F04FAF  Approximate solution of real symmetric positive-definite tridiagonal
%  simultaneous linear equations, one right-hand side (Black Box)
% 
%  F04JGF  Least-squares (if rank = n) or minimal least-squares (if rank < n)
%  solution of m real equations in n unknowns, rank <= n, m >= n
% 
%  F04MAF  Real sparse symmetric positive-definite simultaneous linear
%  equations (coefficient matrix already factorized)
% 
%  F04MBF  Real sparse symmetric simultaneous linear equations
% 
%  F04MCF  Approximate solution of real symmetric positive-definite
%  variable-bandwidth simultaneous linear equations (coefficient matrix
%  already factorized)
% 
%  F04QAF  Sparse linear least-squares problem, m real equations in n unknowns
% 
% 
% 
%  F07 -- Linear Equations (LAPACK)
% 
%  F07ADF  LU factorization of real m by n matrix (SGETRF/DGETRF)
% 
%  F07AEF  Solution of real system of linear equations, multiple right-hand
%  sides, matrix already factorized by F07ADF (SGETRS/DGETRS)
% 
%  F07FDF  Cholesky factorization of real symmetric positive-definite matrix
%  (SPOTRF/DPOTRF)
% 
%  F07FEF  Solution of real symmetric positive-definite system of linear
%  equations, multiple right-hand sides, matrix already factorized by
%  F07FDF (SPOTRS/DPOTRS)
% 
% 
% 
%  G01 -- Simple Calculations and Statistical Data
% 
%  G01AAF  Mean, variance, skewness, kurtosis etc, one variable, from raw
%  data
% 
%  G01ADF  Mean, variance, skewness, kurtosis etc, one variable, from
%  frequency table
% 
%  G01AEF  Frequency table from raw data
%                                                      2
%  G01AFF  Two-way contingency table analysis, with chi /Fisher's exact test
% 
%  G01ALF  Computes a five-point summary (median, hinges and extremes)
% 
%  G01ARF  Constructs a stem and leaf plot
% 
%  G01EAF  Computes probabilities for the standard Normal distribution
% 
%  G01EBF  Computes probabilities for Student's t-distribution
% 
%                                        2
%  G01ECF  Computes probabilities for chi distribution
% 
%  G01EDF  Computes probabilities for F-distribution
% 
%  G01EEF  Computes upper and lower tail probabilities and probability
%  density function for the beta distribution
% 
%  G01EFF  Computes probabilities for the gamma distribution
% 
%  G01FAF  Computes deviates for the standard Normal distribution
% 
%  G01FBF  Computes deviates for Student's t-distribution
% 
%                                       2
%  G01FCF  Computes deviates for the chi distribution
% 
%  G01FDF  Computes deviates for the F-distribution
% 
%  G01FEF  Computes deviates for the beta distribution
% 
%  G01FFF  Computes deviates for the gamma distribution
% 
%  G01HAF  Computes probabilities for the bivariate Normal distribution
% 
% 
% 
%  G02 -- Correlation and Regression Analysis
% 
%  G02BQF  Kendall/Spearman non-parametric rank correlation coefficients,
%  no missing values, preserving input data
% 
%  G02BXF  Computes (optionally weighted) correlation and covariance
%  matrices
% 
%  G02CAF  Simple linear regression with constant term, no missing values
% 
%  G02DAF  Fits a general (multiple) linear regression model
% 
%  G02DGF  Fits a general linear regression model for new dependent variable
% 
%  G02DNF  Computes estimable function of a general linear regression model
%  and its standard error
% 
%  G02FAF  Calculates standardized residuals and influence statistics
% 
%  G02GBF  Fits a generalized linear model with binomial errors
% 
%  G02GCF  Fits a generalized linear model with Poisson errors
% 
% 
% 
%  G03 -- Multivariate Methods
% 
%  G03AAF  Performs principal component analysis
% 
%  G03ADF  Performs canonical correlation analysis
% 
%  G03BAF  Computes orthogonal rotations for loading matrix, generalized
%  orthomax criterion
% 
% 
% 
%  G05 -- Random Number Generators
% 
%  G05CAF  Pseudo-random real numbers, uniform distribution over (0,1)
% 
%  G05CBF  Initialise random number generating routines to give repeatable
%  sequence
% 
%  G05CCF  Initialise random number generating routines to give non-repeatable
%  sequence
% 
%  G05CFF  Save state of random number generating routines
% 
%  G05CGF  Restore state of random number generating routines
% 
%  G05DDF  Pseudo-random real numbers, Normal distribution
% 
%  G05DFF  Pseudo-random real numbers, Cauchy distribution
% 
%  G05DPF  Pseudo-random real numbers, Weibull distribution
% 
%  G05DYF  Pseudo-random integer from uniform distribution
% 
%  G05DZF  Pseudo-random logical (boolean) value
% 
%  G05EAF  Set up reference vector for multivariate Normal distribution
% 
%  G05ECF  Set up reference vector for generating pseudo-random integers,
%  Poisson distribution
% 
%  G05EDF  Set up reference vector for generating pseudo-random integers,
%  binomial distribution
% 
%  G05EHF  Pseudo-random permutation of an integer vector
% 
%  G05EJF  Pseudo-random sample from an integer vector
% 
%  G05EXF  Set up reference vector from supplied cumulative distribution
%  function or probability distribution function
% 
%  G05EYF  Pseudo-random integer from reference vector
% 
%  G05EZF  Pseudo-random multivariate Normal vector from reference vector
% 
%  G05FAF  Generates a vector of pseudo-random numbers from a uniform
%  distribution
% 
%  G05FBF  Generates a vector of pseudo-random numbers from a (negative)
%  exponential distribution
% 
%  G05FDF  Generates a vector of pseudo-random numbers from a Normal
%  distribution
% 
%  G05FEF  Generates a vector of pseudo-random numbers from a beta
%  distribution
% 
%  G05FFF  Generates a vector of pseudo-random numbers from a gamma
%  distribution
% 
%  G05HDF  Generates a realisation of a multivariate time series from
%  a VARMA model
% 
% 
% 
%  G08 -- Nonparametric Statistics
% 
%  G08AAF  Sign test on two paired samples
% 
%  G08ACF  Median test on two samples of unequal size
% 
%  G08AEF  Friedman two-way analysis of variance on k matched samples
% 
%  G08AFF  Kruskal-Wallis one-way analysis of variance on k samples of
%  unequal size
% 
%  G08AGF  Performs the Wilcoxon one sample (matched pairs) signed rank test
% 
%  G08AHF  Performs the Mann-Whitney U test on two independent samples
% 
%  G08AJF  Computes the exact probabilities for the Mann-Whitney U statistic,
%  no ties in pooled sample
% 
%  G08AKF  Computes the exact probabilities for the Mann-Whitney U statistic,
%  ties in pooled sample
% 
%                          2
%  G08CGF  Performs the chi goodness of fit test, for standard
%  continuous distributions
% 
% 
% 
%  G13 -- Time Series Analysis
% 
%  G13AAF  Univariate time series, seasonal and non-seasonal differencing
% 
%  G13ABF  Univariate time series, sample autocorrelation function
% 
%  G13ACF  Univariate time series, partial autocorrelations from
%  autocorrelations
% 
%  G13ADF  Univariate time series, preliminary estimation, seasonal ARIMA
%  model
% 
%  G13AFF  Univariate time series, estimation, seasonal ARIMA model
%  (easy-to-use)
% 
%  G13AGF  Univariate time series, update state set for forecasting
% 
%  G13AHF  Univariate time series, forecasting from state set
% 
%  G13AJF  Univariate time series, state set and forecasts, from fully
%  specified seasonal ARIMA model
% 
%  G13ASF  Univariate time series, diagnostic checking of residuals,
%  following G13AEF or G13AFF
% 
%  G13BAF  Multivariate time series, filtering (pre-whitening) by an
%  ARIMA model
% 
%  G13BCF  Multivariate time series, cross correlations
% 
%  G13BDF  Multivariate time series, preliminary estimation of transfer
%  function model
% 
%  G13BEF  Multivariate time series, estimation of  multi-input model
% 
%  G13BJF  Multivariate time series, state set and forecasts from fully
%  specified multi-input model
% 
%  G13CBF  Univariate time series, smoothed sample spectrum using spectral
%  smoothing by the trapezium frequency (Daniell) window
% 
%  G13CDF  Multivariate time series, smoothed sample cross spectrum using
%  spectral smoothing by the trapezium frequency (Daniell) window
% 
% 
% 
%  M01 -- Sorting
% 
%  M01CAF  Sort a vector, real numbers
% 
%  M01DAF  Rank a vector, real numbers
% 
%  M01DEF  Rank rows of a matrix, real numbers
% 
%  M01DJF  Rank columns of a matrix, real numbers
% 
%  M01EAF  Rearrange a vector according to given ranks, real numbers
% 
%  M01ZAF  Invert a permutation
% 
% 
% 
%  S -- Approximations of Special Functions
% 
%                                z
%  S01EAF  Complex exponential, e
% 
%  S13AAF  Exponential integral E  (x)
%                                1
% 
%  S13ACF  Cosine integral Ci(x)
% 
%  S13ADF  Sine integral Si(x)
% 
%  S14AAF  Gamma function
% 
%  S14ABF  Log Gamma function
% 
%  S14BAF  Incomplete gamma functions P(a,x) and Q(a,x)
% 
%  S15ADF  Complement of error function erfc x
% 
%  S15AEF  Error function erf x
% 
%  S17ACF  Bessel function Y  (x)
%                           0
% 
%  S17ADF  Bessel function Y  (x)
%                           1
% 
%  S17AEF  Bessel function J  (x)
%                           0
% 
%  S17AFF  Bessel function J  (x)
%                           1
% 
%  S17AGF  Airy function Ai(x)
% 
%  S17AHF  Airy function Bi(x)
% 
%  S17AJF  Airy function Ai' (x)
% 
%  S17AKF  Airy function Bi' (x)
% 
%  S17DCF  Bessel functions Y      (z), real a >= 0, complex z,
%                            nu + a
%  nu  = 0,1,2,...
% 
%  S17DEF  Bessel functions J      (z), real a >= 0, complex z,
%                            nu +a
%  nu = 0,1,2,...
% 
%  S17DGF  Airy functions Ai(z) and Ai' (z), complex z
% 
%  S17DHF  Airy functions Bi(z) and Bi' (z), complex z
% 
%                            j
%  S17DLF  Hankel functions H     (z), j = 1,2, real
%                            nu + a
%  a >= 0, complex z, nu  = 0,1,2,...
% 
%  S18ACF  Modified Bessel function K  (x)
%                                    0
% 
%  S18ADF  Modified Bessel function K  (x)
%                                    1
% 
%  S18AEF  Modified Bessel function I  (x)
%                                    0
% 
%  S18AFF  Modified Bessel function I  (x)
%                                    1
% 
%  S18DCF  Modified Bessel functions K      (z), real a >= 0,
%                                     nu + a
%  complex z, nu  = 0,1,2,...
% 
%  S18DEF  Modified Bessel functions I     (z), real a >= 0,
%                                     nu + a
%  complex z, nu  = 0,1,2,...
% 
%  S19AAF  Kelvin function ber x
% 
%  S19ABF  Kelvin function bei x
% 
%  S19ACF  Kelvin function ker x
% 
%  S19ADF  Kelvin function kei x
% 
%  S20ACF  Fresnel integral S(x)
% 
%  S20ADF  Fresnel integral C(x)
% 
%  S21BAF  Degenerate symmetrised elliptic integral of 1st kind R  (x,y)
%                                                                C
% 
%  S21BBF  Symmetrised elliptic integral of 1st kind R  (x,y,z)
%                                                     F
% 
%  S21BCF  Symmetrised elliptic integral of 2nd kind R  (x,y,z)
%                                                     D
% 
%  S21BDF  Symmetrised elliptic integral of 3rd kind R  (x,y,z,r)
%-------------------------------------------
%
%  NAG Foundation Toolbox - Numerical & Statistical Library
% 
%  The ~/nag/examples directory contains example
%  usage for many the functions in the NAG Foundation
%  Toolbox.  Most of the example M-files have the same
%  name as the function they are demonstrating, but with a
%  letter 'e' appended.   The example file for the S21BDF
%  function would be s21bdfe.m.  The rest of the files in
%  the examples directory are helper functions or alternative
%  ways of using the NAG routines.
%

