# Apache Commons Math 3.5

A mathematics and statistics component for the Java programming language, small in size, open sourced, and easy to use and reuse

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What's new in Apache Commons Math 3.3:

- Framework for creating artificial neural nets
- Self organizing feature maps
- Computational geometry algorithms (convex hull, enclosing ball)
- Performance improvements of the linear simplex solver

an update

- LICENSE TYPE:
Apache License

- USER RATING:
- DEVELOPED BY:
**Apache Software Foundation**- HOMEPAGE:
- commons.apache.org
- LANGUAGE:
- Java
- CATEGORY:
- C: \ Scientific/Engineering \ Mathematics

Apache Commons Math can be considered an extension to the Java core and Apache Commons Lang packages, addressing various loopholes regarding mathematical operations and operators.

There are many smaller packages inside the Commons Math component, each targeting one or more niche operation, operator, or algorithm.

Some of the areas the Commons Math packages can be used are:

Documentation is of course included for each of these packages.

There are many smaller packages inside the Commons Math component, each targeting one or more niche operation, operator, or algorithm.

Some of the areas the Commons Math packages can be used are:

*- arithmetic and geometric means*

- variance and standard deviation

- sum, product, log sum, sum of squared values

- minimum, maximum, median, and percentiles

- skewness and kurtosis

- first, second, third and fourth moments

- frequency distributions

- simple regression

- multiple regression

- rank transformations

- covariance and correlation

- statistical tests

- generating random numbers

- generating random vectors

- generating random strings

- generating cryptographically secure sequences of random numbers or strings

- generating random samples and permutations

- analyzing distributions of values in an input file and generating values "like" the values in the file

- generating data for grouped frequency distributions or histograms

- matrix addition, subtraction, multiplication

- scalar addition and multiplication

- transpose

- norm and trace

- operation on a vector

- vector addition, subtraction

- element by element multiplication, division

- scalar addition, subtraction, multiplication, division and power

- mapping of mathematical functions (cos, sin ...)

- dot product, outer product

- distance and norm according to norms L1, L2 and Linf-

- solving linear systems

- eigenvalues/eigenvectors and singular values/singular vectors

- non-real fields (complex, fractions ...)

- root finding

- interpolation

- integration

- numerical analysis

- polynomials

- differentiation

- Erf functions

- Gamma functions

- Beta functions

- double array utilities

- int/double hash map

- continued fractions

- fast mathematical functions

- binomial coefficients, factorials, Stirling numbers and other common math functions

- complex numbers

- complex transcendental functions

- complex formatting and parsing

- probability distributions

- fraction numbers

- fraction formatting and parsing

- transform methods

- 3D geometry

- Euclidean spaces

- n-Sphere

- binary space partitioning

- univariate functions

- ordinary differential equations

- genetic algorithms

- Kalman filter

- curve fitting

- clustering algorithms

- distance measures- variance and standard deviation

- sum, product, log sum, sum of squared values

- minimum, maximum, median, and percentiles

- skewness and kurtosis

- first, second, third and fourth moments

- frequency distributions

- simple regression

- multiple regression

- rank transformations

- covariance and correlation

- statistical tests

- generating random numbers

- generating random vectors

- generating random strings

- generating cryptographically secure sequences of random numbers or strings

- generating random samples and permutations

- analyzing distributions of values in an input file and generating values "like" the values in the file

- generating data for grouped frequency distributions or histograms

- matrix addition, subtraction, multiplication

- scalar addition and multiplication

- transpose

- norm and trace

- operation on a vector

- vector addition, subtraction

- element by element multiplication, division

- scalar addition, subtraction, multiplication, division and power

- mapping of mathematical functions (cos, sin ...)

- dot product, outer product

- distance and norm according to norms L1, L2 and Linf-

- solving linear systems

- eigenvalues/eigenvectors and singular values/singular vectors

- non-real fields (complex, fractions ...)

- root finding

- interpolation

- integration

- numerical analysis

- polynomials

- differentiation

- Erf functions

- Gamma functions

- Beta functions

- double array utilities

- int/double hash map

- continued fractions

- fast mathematical functions

- binomial coefficients, factorials, Stirling numbers and other common math functions

- complex numbers

- complex transcendental functions

- complex formatting and parsing

- probability distributions

- fraction numbers

- fraction formatting and parsing

- transform methods

- 3D geometry

- Euclidean spaces

- n-Sphere

- binary space partitioning

- univariate functions

- ordinary differential equations

- genetic algorithms

- Kalman filter

- curve fitting

- clustering algorithms

- distance measures

Documentation is of course included for each of these packages.

Last updated on April 19th, 2015

Runs on: Windows / Linux / Mac OS / BSD / Solaris

requirements

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