NAG Library For Java Updated
Written by Alex Armstrong   
Tuesday, 11 February 2014

The Numerical Algorithms Group (NAG) has released an updated version of its NAG Library For Java with over 100 additional routines and improved error checking.

Now at  its second release the NAG Library for Java enables the calling of 1,784 mathematical and statistical routines to aid complex computation and now features enhanced error reporting enabling increased precision from computation results.

Release 2 also provides additional abstract classes for callback functions alongside the following new numerical functionality introduced at Mark 24 of the NAG Library

 

  • Multi-start (global) optimization
  • Non-negative least squares (local optimization)
  • Nearest Correlation Matrix
  • Inhomogeneous Time Series
  • Gaussian Mixture Model
  • Brownian Bridge & random fields
  • Best subsets
  • Real sparse eigenproblems
  • Matrix Functions
  • Two-stage spline approximation to scattered data
  • Confluent Hypergeometric Function (pictured below)

The NAG Library offers detailed documentation giving background information and function specification and in addition guides users to the right function for their problem via decision trees.

 

To use the NAG Library you need to have installed a copy of the NAG Fortran Library, available in both  32 and 64-bit versions for Windows and Linux, and to download the NAG Library for Java wrappers. If you are not already a customer you can request a trial version from NAG Software Trials.

 nag

 

More Information

NAG

NAG Library For Java

Related Articles

NAG Updates C Library

New number crunching library - NAG C Mark 9

.NET Version of Mathematical Algorithms

How to number crunch - NAG for .NET

 

blog comments powered by Disqus

 

To be informed about new articles on I Programmer, install the I Programmer Toolbar, subscribe to the RSS feed, follow us on, Twitter, Facebook, Google+ or Linkedin,  or sign up for our weekly newsletter.

 

Banner


Self Paced Haptics MOOC
29/10/2014

Introduction to Haptics is an online self-paced course that introduces a topic increasingly important in robotics and engineering. To get the most out of it you need to build your own Hapkit, an inter [ ... ]



Neural Turing Machines Learn Their Algorithms
05/11/2014

Another breakthrough at Google DeepMind? A neural network form of the Turing machine architecture is proposed and demonstrated, and it does seem to learn its algorithms.


More News

Last Updated ( Tuesday, 11 February 2014 )
 
 

   
RSS feed of news items only
I Programmer News
Copyright © 2014 i-programmer.info. All Rights Reserved.
Joomla! is Free Software released under the GNU/GPL License.