NAG Ping - Issue 43 (February 18, 2005)

This issue covers:

• The NAG Ping is Now NAGNews
• NAG Launches Mark 21 of the NAG Fortran Library
• Getting the Picture, Visualizing Financial Data Part 3
• Data Mining - Getting Over the Hump
• Tech Tips - The NAG Fortran Library, Mark 21
• Product News - New Implementations
• Your privacy - our policy
• Subscribe/Unsubscribe - Manage Your Account
• About The NAGNews
• Contact us / Copyright information

Over the past 4 years, we have been providing NAG customers in North America with The NAG Ping, an e-newsletter containing technical tips for developers, user application stories, up-to-date information on NAG products, and occasional stories about the programs we use every day and the people who wrote them.

We are pleased to announce that this newsletter will now be combined with our sister publication, NAGNews, and will include local as well as global perspectives on the world of technical computing. The NAGNews brings together resources from our offices in Oxford, Chicago and Tokyo, providing our worldwide customers and many friends of NAG with an enhanced e-newsletter about every 6 weeks.

If your organization uses modern spam filtering technology, we suggest that you add nagnews@nag.com to your 'white list' of approved email news providers to ensure that you continue to receive this newsletter.

We are proud to announce the latest version of the NAG Fortran Library which now includes over 250 new functions, taking the total number of routines in Mark 21 to over 1,450. Unrivaled functionality from the routines in the globally renowned NAG Library embraces the world’s most widely used numerical and statistical algorithms.

New functionality includes:

• New chapter of routines for large scale eigenvalue problems
• New solvers for large, sparse systems of linear equations
• Dense linear algebra
  
  • Many new computational and driver routines from LAPACK 3
  • Linear system black-box routines with error bounds
• Statistics: extended coverage including
• Landau and Vavilov distribution and density functions
• Copulas - Normal and Student's t
• Multivariate Normal and Student's t distribution random numbers
• Mixed effects regression
* Stepwise linear regression * Improved quasi-random number generator interfaces
• Extended optimization capabilities including
• Nonlinearly constrained minimization for large sparse problems
• Constrained Quadratic Programming for large sparse problems
• Additions to the Special Functions chapter

Click here to read more about the NAG Fortran Library or email us with any questions at info@nag.com.

Previously, we featured the first two parts of a trilogy of articles by Jeremy Walton, Senior Technical Consultant at NAG, entitled ‘Getting the Picture, Visualizing Financial Data’. An introduction to the third and final part of this collection of articles, which were published in Financial Engineering News is featured below. We’ve also included links to parts one and two below.

In the preceding articles in this series, we saw how visualization can help with the understanding of financial data, and looked at some examples using Microsoft® Excel’s charting function, along with a more advanced visualization package. While Excel is helpful for plotting one variable as a function of another, such as share price vs. time, we saw that data sets that depend on more than one variable - for example, option volatility - require the use of more sophisticated packages which allow for interactivity when slicing through the data, or selecting three-dimensional viewpoints which are used to display the visualization. In addition, we saw that problems arise in Excel when trying to visualize datasets when the spacing between successive values for variables is irregular, or when the data contains discontinuities.

Getting the Picture, Visualising Financial Data Part Three
Getting the Picture, Visualising Financial Data Part Two
Getting the Picture, Visualising Financial Data Part One

Decision trees, neural nets, naïve Bayesian, genetic algorithms... the language of data mining is a brave new world to many of our customers, whether creating applications for internal use or for a commercial product. While the potential is great, many are overwhelmed by the choice of technique, interpreting results, and data preparation issues.

In response, NAG has partnered with EWA Systems of Palo Alto, California to complement the software and expertise already available from NAG. EWA brings over ten years of experience in data mining software creation, application building, and results analysis. EWA’s great strengths are their complete portfolio of pure Java techniques and tools along with their deep expertise in developing solutions for clients in semiconductor manufacturing, customer relationship management, web analytics/personalization and a variety of other fields.

If you would like to learn more about how data mining techniques can provide the insights needed from your data, contact us at info@nag.com and we’ll assemble the right resources from EWA and NAG to address your challenge.

Click here to read more about NAG’s Data Mining & Cleaning Components.

With some implementations of the NAG Fortran Library, Mark 21, now available, it is appropriate to give some general advice.

First, we recommend sites to upgrade to the new release when available. This is because a new release of the Library often includes algorithm improvements and incorporates known bug fixes. Another benefit is, of course, the access to new routines.

NAG never withdraws a routine without adequate notice. In general, at least two marks notice is given of our intention to withdraw a routine. We announce our intentions by placing an asterisk beside the routine name in the relevant chapter contents document.

On receipt of a new Library please be sure to check on the status of routines that you expect to be using over a prolonged period of time. If one of your favorite routines is marked for withdrawal it will have a replacement that we feel is better, so our recommendation is to adapt your program to call this newer routine if at all possible. To help you do this, a document entitled "Advice on Replacement Calls for Withdrawn/Superseded Routines" is available at the front of the manual, in the introductory materials.

If you decide not to do this, then please remember to save the associated documentation for the routine in question. You would be surprised how useful this may be in several years’ time. An executable compiled and linked with a static library implementation of the NAG Library will continue to work indefinitely. Problems will only begin if you subsequently decide to change your program and have not kept the original NAG Library. Shareable libraries are another matter. Because the NAG Library code is not tightly bound into your executables you will need the original library around at all times, if the routine you are calling is no longer in the current library.

NAG Fortran 90 Library (fl90) (Release 4)

• AMD-64 Linux64 using the NAG f90 Compiler

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The NAGNews is an occasional newsletter of technical tips, product information and discussions of technical computing topics.

Contact us at at info@nag.com or http://nag.com/contact_us.asp#northamerica.

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