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.
(Summation of Series
) has Fast Fourier Transforms (FFTs) for two-dimensional and three-dimensional real data.
) has three-dimensional discrete wavelet transforms.
) has a comprehensive one-dimensional adaptive quadrature function and a variant for badly behaved integrands.
(Ordinary Differential Equations
) has threadsafe versions of the suite implementing Runge–Kutta methods.
) has the modified Shepard's method for interpolating in dimensions greater than 5
(Curve and Surface Fitting
) has a two-stage approximation method for two-dimensional scattered data.
(Minimizing or Maximizing a Function
) has non-negative least squares and an improved MPS data reader.
(Global Optimization of a Function
) has multi-start versions of general nonlinear programming and least squares functions.
(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.
(Eigenvalues and Eigenvectors
) has a driver function for calculating selected eigenvalues/vectors of general sparse matrices.
(Simultaneous Linear Equations
) has norm estimators for rectangular matrices.
(Large Scale Linear Systems
) has a block diagonal (possibly overlapping) preconditioner and associated solver for real and complex nonsymmetric sparse matrices.
(Large Scale Eigenproblems
) has a driver for selected eigenvalues/vectors of general banded complex eigenproblems.
(Further Linear Algebra Support Routines
) has two additions from the BLAST set of functions.
(Simple Calculations on Statistical Data
) has functions for combining summary statistics from blocks of data, probabilities from a multivariate Student's t
-distribution, and a large set of vectorized versions of functions for probabilities and density functions.
(Correlation and Regression Analysis
) has functions for weighted nearest correlation matrix and combining two sums of squares.
) has a Gaussian mixture model function.
(Random Number Generators
) has Brownian bridge and random field functions.
(Time Series Analysis
) has moving averages for inhomogeneous time series.
) has functions for computing best subsets.
(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
© The Numerical Algorithms Group Ltd, Oxford, UK. 2009–2013