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Chapter Contents
NAG Toolbox

News (NAG Toolbox Mark 24)

At Mark 24 of the NAG Toolbox new functionality has been introduced in addition to improvements in existing areas.
There have been extensions in functionality included in the areas of statistics, wavelets, ordinary differential equations, interpolation, surface fitting, optimization, matrix operations, linear algebra, operations research, and special functions.
Chapter C06 (Summation of Series) has Fast Fourier Transforms (FFTs) for two-dimensional and three-dimensional real data.
Chapter C09 (Wavelet Transforms) has three-dimensional discrete wavelet transforms.
Chapter D01 (Quadrature) has a comprehensive one-dimensional adaptive quadrature function and a variant for badly behaved integrands.
Chapter D02 (Ordinary Differential Equations) has threadsafe versions of the suite implementing Runge–Kutta methods.
Chapter E01 (Interpolation) has the modified Shepard's method for interpolating in dimensions greater than 55.
Chapter E02 (Curve and Surface Fitting) has a two-stage approximation method for two-dimensional scattered data.
Chapter E04 (Minimizing or Maximizing a Function) has non-negative least squares and an improved MPS data reader.
Chapter E05 (Global Optimization of a Function) has multi-start versions of general nonlinear programming and least squares functions.
Chapter F01 (Matrix Operations, Including Inversion) has greatly extended its range of matrix function functions including the calculation of condition numbers and the action on another matrix.
Chapter F02 (Eigenvalues and Eigenvectors) has a driver function for calculating selected eigenvalues/vectors of general sparse matrices.
Chapter F04 (Simultaneous Linear Equations) has norm estimators for rectangular matrices.
Chapter F11 (Large Scale Linear Systems) has a block diagonal (possibly overlapping) preconditioner and associated solver for real and complex nonsymmetric sparse matrices.
Chapter F12 (Large Scale Eigenproblems) has a driver for selected eigenvalues/vectors of general banded complex eigenproblems.
Chapter F16 (Further Linear Algebra Support Routines) has two additions from the BLAST set of functions.
Chapter G01 (Simple Calculations on Statistical Data) has functions for combining summary statistics from blocks of data, probabilities from a multivariate Student's tt-distribution, and a large set of vectorized versions of functions for probabilities and density functions.
Chapter G02 (Correlation and Regression Analysis) has functions for weighted nearest correlation matrix and combining two sums of squares.
Chapter G03 (Multivariate Methods) has a Gaussian mixture model function.
Chapter G05 (Random Number Generators) has Brownian bridge and random field functions.
Chapter G13 (Time Series Analysis) has moving averages for inhomogeneous time series.
Chapter H (Operations Research) has functions for computing best subsets.
Chapter S (Approximations of Special Functions) has added special functions: confluent hypergeometric, log beta and incomplete beta; additionally a large set of vectorized versions of existing special functions.

Further details of changes


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