Simulate toll gates queues on Mathematica 7.
Stand-alone software tool for the interactive CE analysis of microarray data. The software is a user-friendly and allows on-the-fly study of CE
CORe microBiome Analysis Tools
Corbata is a set of statistical tools that can be used to analyze the core microbiome across a set of samples.
Java Swing based GUI for R statistical language
Software to cluster protein sequences into functionally similar groups. Journal reference: http://bioinformatics.oxfordjournals.org/cgi/content/short/24/16/1765
Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
A command line toolki to solve a problem your favorite program defines
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
Dissolution Kinetics Software Excel Based
A project aims to develop a system which trains LDA model in distributed enviorenment. I studied Hadoop based solution and found that Hadoop is not fit for distributed LDA training case. In this project I implement a platform based on socket.
"DoomsdayCalculator" is based on the doomsday argument and allows the user to calculate minimum and maximum expected remaining lifetimes at a certain confidence level.
The EconoMind is a utility that simulates the economy of a city, state, country, or planet at a specific level of technological development. It runs behind the scenes and provides supply, demand, and other information for games and other projects.
The procedure of building the environment of Emacs + ESS for R is more complicated, so we exploit the automated installation software that combines R, Emacs and ESS to let the the public download and install.
PHP implementation of General Purpouse Surveys Editor, Collector and Analizer of Data.
An R Package for Environmental Statistics
EnvStats is an R package for environmental statistics. It is the open-source successor to the commercial module for S-Plus© called "EnvironmentalStats for S-Plus", which was first released in April, 1997. The EnvStats package, along with the R software environment, provides comprehensive and powerful software for environmental data analysis. EnvStats brings the major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. Also included are numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!”
Event studies in several statistical packages
Software to perform event studies in several statistical packages, such as SAS, Stata and R.
Excel + Cytoscape + R = ExCytR = magical unicorn networks
This project (under construction) combines Excel (and other spreadsheet apps.) , Cytoscape and R to make magical data visualizations in the form of networks.
This project adds a ribbon to excel with a number of statistical buttons. This is not intended to be a full statistical analysis package (like R), but only a source for quick visualizations and calculations. For Excel2007 and up
GUI based toolkit for running common Machine Learning algorithms.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model.
F@H League Web App is a simple ASP.Net Web application that allows you to create a League of Folding@Home Teams you are interested in and view a range of league tables, statistics and Graphs.
Facinas: Probabilistic Graphical Models is an extensive set of librairies, algorithms and tools for Probabilistic Inference and Learning and Reasoning under uncertainty. It implements all sort of Probabilistic Graphical Models using discrete and continuous distributions.
FastPval is multiple stage p-value computing software that computes empirical p-values from a large set of permutated/resampled background data.
Command line fibonacci series calculation program.
Scientific research work of Francesco Montorsi,Univ. of Modena, Italy
This project hosts the code and the documents which were created by Francesco Montorsi during his PhD at the University of Modena and Reggio Emilia, Italy, about indoor and outdoor localization and navigation techniques. The code (mostly MATLAB code) is publicly available to enable reproducible research.
Freegressi est un logiciel pour tracer des courbes de tendances à partir de séries de données.
Global nonlinear optimization with automatic differentiation
NOTE: Development continued at GitHub! Current version is higher than 1.2.0. GADfit is a Fortran implementation of global nonlinear curve fitting, based on a modified Levenberg-Marquardt algorithm. Global fitting refers to fitting many datasets simultaneously with some parameters shared among the datasets. The fitting procedure is very fast and accurate thanks to the use of automatic differentiation. The model curves (fitting functions) can be of essentially arbitrary complexity. This includes any nonlinear combination of elementary and special functions, single and/or double integrals, and any control flow statement allowed by the programming language. See the latest user guide under Files.