Numerical Analysis Library

A Numerical Analysis Library is a numerical analysis software that is a domain-specific software library (that implements and provides an interface to numerical analysis algorithms).

• AKA: Numerical Approximation Library.
• Context:
  • It can be used to solve a Numerical Analysis Task.
  • It can be used to build a Numerical Analysis-based System.
  • It can be a member of a Numerical Analysis Environment.
• Example(s):
  • a Linear Algebra Library, if it includes Linear Algebra Algorithms.
  • a Statistical Analysis Library, if includes Statistical Analysis Algorithms.
  • a Numerical Optimization Library, if it includes Numerical Optimization Algorithms.
  • a Python, Scala, R, Java, C++, Fortran, ...
  • …
• Counter-Example(s):
  • a Numerical Analysis Development Environment, such as MATLAB, Mathematica, Maple, GNU Octave, SAS, and R Development Environment.
  • Numerical Analysis Programming Environment, like MATLAB.
  • Numerical Software Package, Numerical Software Analysis, Numerical Analysis.
  • a Statistics Library.
  • a Machine Learning Library.
• See: Numerical Linear Algebra, Numerical Analysis Programming Language, Systems of Linear Equations, Numerical Methods For Linear Least Squares, Eigendecomposition of a Matrix, Singular Value Decomposition, Matrix Factorization, LU Decomposition, QR Decomposition, Cholesky Decomposition, Schur Decomposition.

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References

• http://en.wikipedia.org/wiki/Category:Numerical_libraries

2014

• http://en.wikipedia.org/wiki/List_of_numerical_libraries
  • This is a list of notable numerical libraries, which are libraries used in software development for performing numerical calculations. It is not a complete list of numerical libraries, but is instead a list of numerical libraries with articles on Wikipedia, with few exceptions.

    The Choice of a typical library depends on a diverse range of requirements such as: desired features (for e.g.: large dimensional linear algebra, parallel computation, partial differential equations), commercial/opensource nature, readability of API, portability or platform/compiler dependence (for e.g.: Linux, Windows, Visual C++, GCC), performance in speed, ease-of-use, continued support from developers, standard compliance, specialized optimization in code for specific application scenarios or even the size of the code-base to be installed.

    As we find comprehensive surveys rarely available, there is almost always (at least initially) a difficult choice among a number of possible libraries. Often it tends to be at the discretion of the user based on his own taste and comforts, only due to the lack of proper information.

2011

• http://en.wikipedia.org/wiki/List_of_numerical_libraries
  • List of numerical libraries used for performing numerical calculations:

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