Open Source Linux Statistics Software

libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported.

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.

MXLib is a C++ wrapper around the Intel® Integrated Performance Primitives (IPP) library and NVidia NPP CUDA library. You can use either IPP code (or a subset of functions that do not require IPP) on the CPU side, or use NPP/CUDA on the GPU side, or use both together. The function syntax is similar to that found in MatLab and the library is designed to make it easy to port your code from MatLab to C++. The idea is to provide Scientists, Engineers, Researchers and other non full-time programmers an easy to use, high performance library of functions.

Diagonal can be used for: - getting descriptive statistics such as mean/median/mode with your program producing a sample - finding a root of an equation your program defines - calculating a fixed point of a function your program defines - detecting a cycle of a fuction your program defines as well as - decoding a VCDIFF file

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

IterInt is a numerical integration package that implements iterated numerical integration methods. Iterated methods can be used to compute low dimensional (less than ten, for example) integration problems to get very accurate results.

An R package for detailed inspection and analysis of LCMS data. An R package developed by Sukhdeep Singh at Department of Surgery and Cancer, Imperial College London,UK.

Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes.

An R package implementation of a consensus clustering methodology. This package allows users to perform re-sampling statistics based clustering using multiple clustering algorithms to assess the robustness of both clusters and members of clusters.

CTSA is a C software package for univariate time series analysis. This is a work in progress. ARIMA and Seasonal ARIMA models have been added so far. Other functionality will be added soon . Documentation - https://github.com/rafat/ctsa/wiki

Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.

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.

Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.

This project is goaled a r-language wrap of Artificial Neural Network library libfann. also known as R-binding libfann