Open Source Linux Statistics Software - Page 3

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.

Implementation of the A2RMS Algorithm for univariate densities defined for real values.

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).

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.

ASEP simulation library is specialized for simulations of Asymmetric Simple Exclusion Processes (ASEP) and its mutations like SSEP or TASEP based on a graph. It is consisted of agents, models, timers and graphs that forms united modelling enviroment ready for computer cluster use - all based on Zarja library.

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++.

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.

Linear Programming (LP) has been used in the case of the Federalist Papers whose authorship had been disputed. The task here will be to use the Cell Broadband Engine to do likewise with papers whose authorship is disputed.

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.

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).

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.

Blueprint XAS is a Matlab-based suite designed for the processing and analysis of near-edge x-ray absorption spectroscopy (XAS) data. The suite is designed primarily to assist users in exploring reasonable fit solutions while minimizing user bias.

A collection of different methods for implementing in C++ polycrystalline growth for metals during annealing or recrystallization.

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.

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).

That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.

A library based on Eigen and Boost to handle common multivariate distributions in C++

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.

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).

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.

The CRISP package here developed utilizes an algorithm that describes a many-body intranuclear cascade (INC) and evaporation/fission/multifragmentation competition process.

Un piccolo tool in java per effettuare calcoli combinatori come: -Disposizioni -Permutazioni -Combinazioni Calcolo Combinatorio Java

Simulate toll gates queues on Mathematica 7.

The CausalImpact repository houses an R package that implements causal inference in time series using Bayesian structural time series models. Its goal is to estimate the effect of an intervention (e.g. a marketing campaign, policy change) on a time series outcome by predicting what would have happened in a counterfactual “no intervention” world. The package requires as input a response time series plus one or more control (covariate) time series that are assumed unaffected by the intervention, and it divides the time horizon into “pre-intervention” and “post-intervention” periods. It uses Bayesian modeling to fit a structural time series to the pre-period and extrapolate a counterfactual prediction for the post period, then compares observed vs predicted to infer the causal effect. The package supports plotting, summary tables, and verbal narratives for interpretive reports.