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ILNumerics started in 2006 as an open source project, originating from Technische Universität Berlin. [1] In 2007 ILNumerics won the BASTA! Innovation Awards 2007 [2] as most innovative .NET project in Germany, Switzerland and Austria. After 6 years of open source development, the project added a closed source, proprietary license in 2011 ...
Product One-way Two-way MANOVA GLM Mixed model Post-hoc Latin squares; ADaMSoft: Yes Yes No No No No No Alteryx: Yes Yes Yes Yes Yes Analyse-it: Yes Yes No
Programmable, direct support of 2D+3D plotting. Interfaces to many other software packages. Interfacing to external modules written in C, Java, Python or other languages. Language syntax similar to MATLAB. Used for numerical computing in engineering and physics. Smath Studio: SMath LLC (Andrey Ivashov) 2006 1.0.8348 11 September 2022: Free
The random matrix R can be generated using a Gaussian distribution. The first row is a random unit vector uniformly chosen from S d − 1 {\displaystyle S^{d-1}} . The second row is a random unit vector from the space orthogonal to the first row, the third row is a random unit vector from the space orthogonal to the first two rows, and so on.
In early 2005, NumPy developer Travis Oliphant wanted to unify the community around a single array package and ported Numarray's features to Numeric, releasing the result as NumPy 1.0 in 2006. [9] This new project was part of SciPy. To avoid installing the large SciPy package just to get an array object, this new package was separated and ...
ELKI a software framework for development of data mining algorithms in Java. GAUSS, a matrix programming language for mathematics and statistics. GNU Data Language, a free compiler designed as a drop-in replacement for IDL. IDL, [21] a commercial interpreted language based on FORTRAN with some vectorization.
[1] [2] In other words, () is the probability that a normal (Gaussian) random variable will obtain a value larger than standard deviations. Equivalently, Q ( x ) {\displaystyle Q(x)} is the probability that a standard normal random variable takes a value larger than x {\displaystyle x} .
JAX is a machine learning framework for transforming numerical functions. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).