Search Results for "statistics algebra"
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Showing 15 open source projects for "statistics algebra"
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1
SymPy
A computer algebra system written in pure Python
SymPy is an open source Python library for symbolic mathematics. Its goal is to become a full-featured computer algebra system (CAS) while maintaining the simplicity of its code. Written entirely in Python, SymPy is easy to use, comprehensible and easily extensible. It’s also very lightweight as it solely depends on mpmath, a pure Python library for arbitrary floating point arithmetic. SymPy has participated in every Google Summer of Code since 2007 and because of this has continuously... -
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MathPHP
Powerful modern math library for PHP
Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing. -
3
Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. -
4
SciPy
SciPy library main repository
This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. ... -
Component Content Management System for Software DocumentationPaligo is an end-to-end Component Content Management System (CCMS) solution for technical documentation, policies and procedures, knowledge management, and more.
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5
Gonum
Set of numeric libraries for the Go programming language
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more. Gonum is a set of packages designed to make writing numerical and scientific algorithms productive, performant, and scalable. Gonum contains libraries for matrices and linear algebra; statistics, probability distributions, and sampling; tools for function differentiation, integration, and optimization; network creation and analysis; and more. ... -
6
Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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stkpp
C++ Statistical ToolKit
STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. -
9
Agena
Agena is an interpreted procedural programming language.
Agena is an easy-to-learn procedural programming language designed for science, scripting, and many other applications. Binaries are available for Windows, Linux, Solaris, OS/2, Mac OS X, Raspberry Pi and DOS. -
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10
mmmv_set_of_WinXP_SP3_x86_installers_t1
Yet another collection of WindowsXP ServicePack3 x86 binaries.
The binaries have been downloaded in 2023 summer and autumn from various places without checking the downloaded binaries for malware. There was an effort to download the binaries from original authors'/publishers' web sites, but if the original publishing web site could not be found or it lacked sufficiently old versions, then almost any random download site was used. -
11
PLP_Solvers
Library of solvers for work in Science, Engineering & Education
Portable library of solvers for work in Science, Engineering & Education. Library Contents: High Precision Computation, Numerical Calculus, Complex Analysis, Geometry, Linear Algebra, Special Functions, Differential Equations, Transformations, Optimization & Interpolation, Statistics, Physics ... (12,538 functions in v23.06 package) Knowledge of any programming language is not required. Only Windows port is available. -
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TheoremJS
A Math library for computation in JavaScript
TheoremJS is a mathematical framework that is packed up with tons of useful mathematical functions. It is composed of functions in most mathematical fields such as algebra, number theory, statistics, etc... It was designed to fit your need, whatever you are trying to do. With TheoremJS, you won't feel the need of running the code on a server, you can run it right on the browser, or on a NodeJS notebook (Jupyter like). Even though we loose performances with BigNumber, our algorithms are well-engineered and ensure decent performances on every device. ... -
13
msp
mathSuite Speed & Matrix Stream Processor
This program is fundamentally a short-sized version of my mathSuite program: https://sourceforge.net/projects/mathsuite/ It includes all the functionalities of MSCenv (mathSuite Calculus Environment), such as inline variables and functions (mainly thanks to ExprEval), which you can use to perform expensive complex computations and store their results into runtime variables. You can perform also every Linear Algebra Operations included in mathSuite with new optimizations. -
14
math toolkit
A C++ and Python library for finance, statistics and linear algebra.
A lightweight C++ and Python library for finance, statistics and linear algebra. Finance features include compound rate present/future value, annuity, various present/future value coefficients ... Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... ... -
15
This project examines techniques to model three-dimensional rigid body motion using the geometric algebra of Dual Quaternions and how such models compare to more traditional models when used in underconstrained filtering applications.
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