The NAG Toolbox for MATLAB provides a solid numerical foundation and serves diverse mathematical areas. It is expertly documented, maintained and supported, and is regularly updated with cutting edge algorithmic capabilities.
One of the key benefits to MATLAB users using the NAG Toolbox for MATLAB is the extensive routine documentation for every routine accessible from the Toolbox. Included in the documentation for each NAG Library routine is example MATLAB code showing how to call the routine. The index is provided in HTML format and each routine's documentation includes a link to a printable PDF file.
To illustrate how easy the NAG Toolbox for MATLAB is to use, we demonstrate how to call NAG routines, and use MATLAB's plotting facilities to view the results:
- Finding the root of an equation (C05 Chapter)
- Interpolation through a set of points (E01 Chapter)
- Fitting a surface with bicubic splines (E02 Chapter)
- Fitting a set of points with a cubic spline (E02 Chapter)
- Minimization of a function (E04 Chapter)
- Quadrature (D01 Chapter)
- Creating a Gaussian copula (G Chapter)
- Multivariate Methods (G03 Chapter)
- Random Number Generators (G05 Chapter)
- Time series analysis (G13 Chapter)
- Bessel functions (S Chapter)
"I am impressed by the optimization algorithm provided by the NAG Toolbox for MATLAB. It improves the results for my maximum likelihood estimations for situations where the sample size is small causing non-concentrating likelihood and when the likelihood functions have 'ridges'. Ordinary algorithms, for example Newton gradient search, perform poorly in these situations."