Search Results for "linear"
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Showing 26 open source projects for "linear"
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
...The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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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. ... -
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Napkin
An Infinitely Large Napkin
...It is not a polished textbook full of full proofs; rather it offers clean definitions, theorem statements, intuitive motivations, and informal sketches of why things work, with the goal of building conceptual understanding. The coverage spans undergraduate and early graduate topics, designed to show how different areas of math fit together—linear algebra, analysis, topology, number theory, and more—without going deeply into every subtopic. Because it is written in LaTeX (with supporting Asymptote or other tools), readers can compile their own version, and the repository integrates diagrams, flowcharts, and supplementary files. -
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MCPower
MCPower — simple Monte Carlo power analysis for complex models
...It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). Supports both standard linear models and mixed-effects models. Additional features include analysis history, configurable scenarios, and built-in documentation. -
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Digraph3
A collection of python3 modules for Algorithmic Decision Theory
This collection of Python3 modules provides a large range of implemented decision aiding algorithms useful in the field of outranking digraphs based Multiple Criteria Decision Aid (MCDA), especially best choice, linear ranking and absolute or relative rating algorithms with multiple incommensurable criteria. Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. ... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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3d Linear Transformation Visualization
Visualize 3d linear transformations.
A linear transformation is a function from one vector space to another that respects the linear structure of each vector space. For visualizing this we can transform a vector, but it has an obvious problem, because the linear transformation transform the whole space, not just the vector, in other words it transforms the basis vectors thus every vector in the space gets transformed too. -
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Awesome Math
This is the Curriculum for "How to Learn Mathematics Fast"
This repository is a curated roadmap for learning the core mathematics used in computer science, machine learning, and data science without getting lost in unnecessary detours. It organizes topics like algebra, calculus, linear algebra, probability, and statistics into a pragmatic sequence that favors intuition and problem-solving over purely formal proofs. The materials emphasize short, high-leverage resources—video lectures, concise notes, and hands-on exercises—that help you build momentum quickly. It also suggests checkpoints and practice ideas so you can test comprehension and move forward with confidence. ... -
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...The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.
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math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
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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 ... ... -
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ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid
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Fulguro is an optimized 2D library for image processing with Mathematical Morphology and Linear processing
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A module containing python wrappers for the SUite of Non-linear DIfferential/ALgebraic Solvers (SUNDIALS), using ctypes.
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A Python environment for large and sparse linear and nonlinear optimization using intuitive interfaces to linear algebra tools and subproblem solvers written in low-level languages. It provides building blocks to experiment with new ideas and algorithms.
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Linear Algebra Common Expressions (LACE) is a C++ templated library which allows you to operate with matricies and vectors inside your code as easy as on the whiteboard.
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PuLP: An LP modeller in Python PuLP is an LP modeller written in python. PuLP can generate MPS or LP files and call GLPK, COIN CLP/CBC, CPLEX and XPRESS to solve linear problems.
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Improved version of the LibNumTh library (http://libnumth.sourceforge.net/), reimplementing its methods to work concurrently in a SMP environment. In addition, it is extended with support for linear algebra and numerical methods mechanisms.
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MathGL++ is a class library for fast C++ maths for use in OpenGL C++ projects. Easy to use and similar to the OpenGL API. Matricies, Vectors, Quaternions, Linear polynomials with eigen systems are all going to be included.
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Mos2Gnu is a conversion utility to generate a GNU MathProg description file, understandable by the GNU Linear Programming Kit from the proprietary X-Press Mosel's file format
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Traditional but powerful cross-platform calculator. It is written in python and it uses wxWidgets as GUI (project is developed with Boa Constructor). By use of SciPy the vaCalculator can solve linear systems, do math with polynomials, integration etc.
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Port of Numerical Python to Jython (Java Python) to support all mathematical operations (linear algebra, matrices, DSP, wavelets, FFT, arrays...) and thus compete with commercial packages such as Matlab. It can be easily embedded in Java programs.
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MatPy is a Python package for numerical linear algebra and plotting with a MatLab-like interface. It currently consists of wrappers around Numeric and Gnuplot packages, but eventually may be implemented directly in C/C++, or as interface to Octave.
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Central schemes offer a simple and versatile approach for computing approximate solutions of non-linear systems of hyperbolic conservation laws and related PDEs.
