Open Source Windows Statistics Software - Page 3
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Statistics Software for Windows
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TU Calc
Simple tool for numerical calculation
TU Calc is a modular tool that aims to gather numerical methods for solution of mathematical problems. Interacting with the user through a GUI that is analogous to the windows desktop. -
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abc-sde
approximate Bayesian computation for stochastic differential equations
A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/ -
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Statistical models with python using numpy and scipy. Currently covers linear regression (with ordinary, generalized and weighted least squares), robust linear regression, and generalized linear model, discrete models, time series analysis and other statistical methods.
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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. The library offers a dense set of (mostly) template classes in C++ and is suitable for projects ranging from small one-off projects to complete data mining application suites. -
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MandelbrotExplorer
A program to calculate and represent the Mandelbrot set
This project is a C++ program to calculate and represent graphically the Mandelbrot fractal set, and/or the corresponding Julia sets, according to the seed Z0 given by the user as input. The user disposes of a graphical interface to control the program and modify conveniently some parameters, like the XY-scales, the XY map area, the Julia seed for the complex series iteration of Z(n+1)=Z(n)^2+a, being Z(0)=(X0,Y0) the seed, and "a in XY" the points to be calculated. The user can enter (among other parameters) the desired convergence-radius R for the series, and/or the number of maximal iterations N for the generator-equation in Z. -
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A2RMS Algorithm
Implementation of the A2RMS Algorithm in Matlab
Implementation of the A2RMS Algorithm for univariate densities defined for real values. -
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The Automated Parameter Estimation and Model Selection Toolkit is a fast, parallelized MCMC engine written in C for Bayesian inference (parameter estimation and model selection).
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ARNU
Arredondamento de Números
Sistema de Apoio Didático Profissional. ARNU - Arredondamento de Números. O aplicativo ARNU tem por objetivo auxiliar na resolução de cálculos de arredondamento matemático, abordados de forma técnica, entregando ao usuário um resultado didático e objetivo, o motivo e as normas utilizadas. -
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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation routines. It is written in C++. -
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A alternative to the SAS Viewer written in SAS/AF. First presented on 2010-10-05 in BASAS meeting. With extended abilities in sorting, filtering, simple frequency count, statistics and various data review oriented features.
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A collection of compact, powerful programs and functions, written in C, for the analysis and transformation of data. No object or structure dependencies, no fancy interfaces - just good tools.
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Assisted dRawing toOl
ARO helps physically disabled students to create mathematical drawings
ARO has been developed to assist physically disabled or injured students who cannot create mathematical drawings on paper. It is intended to make maths up to Key Stage 4 more accessible. AQA has agreed to its use in a GCSE maths exam. Anyone who can use a computer with a mouse to access the internet should be able to use ARO. The processes required mimic those of on paper drawing as far as possible. Possible applications include: Graphs of straight lines and smooth curves Compass and ruler constructions Scatter graphs Stem and leaf displays Box plots Histograms Pie charts Simple diagrams. The structure of each drawing is built from individual components which can be placed on the drawing grid without great accuracy. Each can then be positioned exactly using onscreen buttons. The ruler and the protractor can be aligned with any straight line. Drawings can be created on imported background bitmaps. The author was a mathematics lecturer at Plymouth University. -
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BACE for gretl
Bayesian Averaging of Classical Estimates
Bayesian Averaging of Classical Estimates package. -
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BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
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Benchee
Easy and extensible benchmarking in Elixir
Library for easy and nice (micro) benchmarking in Elixir. Benchee allows you to compare the performance of different pieces of code at a glance. It is also versatile and extensible, relying only on functions. There are also a bunch of plugins to draw pretty graphs and more! Benchee runs each of your functions for a given amount of time after an initial warmup, it then measures their run time and optionally memory consumption. It then shows different statistical values like average, standard deviation etc. The aforementioned plugins like benchee_html make it possible to generate nice-looking HTML reports, where individual graphs can also be exported as PNG images. first runs the functions for a given warmup time without recording the results, to simulate a "warm"/running system. Plugin/extensible-friendly architecture so you can use different formats to display benchmarking results as HTML, markdown, JSON, and more. -
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BiomeNet
BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES
Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). -
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Black Hole Cortex
Sphere surface layers of visual cortex approach maximum info density
Near the surface (even horizon) of a black hole, there is maximum information density in units of squared plancks (and some translation to qubits). Similarly, our imagination is the set of all possible things we can draw onto our most dense layer of visual cortex in electricity patterns. Bigger layers have more neurons to handle those possibilities. A Black Hole Cortex is a kind of visual cortex that has density of neuron layers similar to density at various radius from a black hole. What we think our eyes see, the imagination, is the densest and smallest layer. SphereSurfaces outside it recursively have more neurons, more surface area, but less density since it has to eventually dimension-reduce to high level ideas, like there are 10000 Wikipedia page names that cover most parts of the world. We can think of Wikipedia as a layer above our brains, a global SphereSurface of large surface area (a cortex layered on billions of minds) and small (10000 most important pages) density. -
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A collection of different methods for implementing in C++ polycrystalline growth for metals during annealing or recrystallization.
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Calculates how much time and money you need to win in the lottery. It uses multiple gthreads and gtk2 to sort 1 to 50 numbers until the user wins. Asking for the cost and time beetwin games, it calculates if you or your grandchildren will be rich.
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That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline-related Inventory Management system. That library uses the Standard Airline IT C++ object model (http://sf.net/projects/stdair).
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C++ Multivariate Distributions Library
A Multivariate Distributions Package for C++
A library based on Eigen and Boost to handle common multivariate distributions in C++ -
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That project aims at providing a clean API and a simple implementation, as a C++ library, of a Travel-oriented fare engine. It corresponds to the simulated version of the real-world Fare Quote System.
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That project aims at providing a clean API and a simple implementation, as a C++ library, of a Travel-oriented Distribution System. It corresponds to the simulated version of the real-world Computerized Reservation Systems (CRS).
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A population-based method for DNA copy number analysis: recurrent copy number aberration indentification in multiple samples (with no need of single-sample calling). Developed for a quick analysis of high resolution and large population data.
