Statistics Software

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Statistics Software

  • 2018 Thomson Reuters Top 100 Global Tech Leaders 2018 Thomson Reuters Top 100 Global Tech Leaders Icon
    2018 Thomson Reuters Top 100 Global Tech Leaders Icon

    See how tech-sector leadership is being redefined in today’s complex business environment.

    21st century technology-sector leadership requires not only optimal financial performance but also attention to many other factors, including management and investor confidence, risk and resilience, legal compliance, innovation, environmental impact, social responsibility, and reputation. Successfully managing these areas may determine which tech companies have the fortitude to succeed in the future. Here’s to those that made the list.
    Who are today’s top global tech leaders?
    Read the report
  • SOFA Statistics

    SOFA is a statistics, analysis, and reporting program with an emphasis on ease of use, learn as you go, and beautiful output.

  • RGedit

    Please participate in the SURVEY on rgedit's future: https://www.surveymonkey.com/s/VNMMJMJ your answers are much appreciated! Gedit (Gnome editor, www.gedit.org) plug-in allowing it to become an easy-to-use and yet light-weight IDE for the statistical programming environment, R (www.r-project.org).

  • SalStat Statistics Package

    SalStat is a small application for statistical analysis emphasising the sciences and social sciences (particularly Psychology). The project is designed around the user interface which has been designed to be simple to use. Think SPSS, but better!

  • MinimPy

    MinimPy is a desktop application program for sequential allocation of subjects to treatment groups in clinical trials by using the method of minimisation. Comprehensive reference help is available at: http://minimpy.sourceforge.net For those who have difficulty installing MinimPy, an online version is available at: http://qminim.sourceforge.net MinimPy has been full described in the foolowing article: Saghaei, M. and Saghaei, S. (2011) Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. Journal of Biomedical Science and Engineering, 4, 734-739. doi: 10.4236/jbise.2011.411090. Available at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=8518

  • MBlock

    1. Create an object-oriented python script that can represent mathematical concepts and their properties. 2. Represent all numeric values exactly. 3. Provide a variety of formats to export or embed representations of the mathematical concepts.

    Downloads: 3 This Week Last Update: See Project
  • C++ Airline Inventory Management Library Icon

    C++ Airline Inventory Management Library

    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).

    Downloads: 1 This Week Last Update: See Project
  • BayesExplore

    A python based Bayesian network implementation. This project aims to provide a single point of entry-solution for searching through available networks matching data and optimizing CPT's.

    Downloads: 0 This Week Last Update: See Project
  • C++ Airline Travel Market Simulator Icon

    C++ Airline Travel Market Simulator

    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.

  • C++ Simulated Fare Quote System Library Icon

    C++ Simulated Fare Quote System Library

    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.

  • C++ Simulated Travel Distribution System Icon

    C++ Simulated Travel Distribution 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).

    Downloads: 0 This Week Last Update: See Project
  • DeDAY Icon

    DeDAY

    MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.

    DeDAY (Demography Data Analyses) is a tool of analyzing demography data. It supports Gompertz, Weibull and Logistic distributions. DeDay also supports mixed mortality models based on these distribution such as the Gompertz-Makeham distribution. Distributions such as Gompertz describes only age-dependent mortality, which increases over time. Mixed mortality models, such as in Gompertz-Makeham distribution, consider a more general case where mortality is consist of both age-dependent and in-dependent mortality. Mixed models partition mortality into exogenous and endogenous components, so that the intrinsic survivorship can be estimated without the interference from extrinsic noise. DeDAY supports both interval-censored data and exact event-time data. Using MLE (Maximum Likelihood Estimate), DeDAY fits statistic model to the data. DeDAY also calculates the variances and the multi-dimensional confidence limits of model parameters. DeDAY is free for academic users.

    Downloads: 0 This Week Last Update: See Project
  • ExoPlanet Icon

    ExoPlanet

    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.

    Downloads: 0 This Week Last Update: See Project
  • Facinas: Probabilistic Graphical Models

    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.

    Downloads: 0 This Week Last Update: See Project
  • Gaussian Mixture Distribution Analysis

    This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.

    Downloads: 0 This Week Last Update: See Project
  • HypSurGent

    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.

    Downloads: 0 This Week Last Update: See Project
  • OpenStats Icon

    OpenStats

    Set your statistical data free!

    Manage statistical data using an editor written in the open source Python programming language and save files in a portable CSV format.

    Downloads: 0 This Week Last Update: See Project
  • PaCal Icon

    PaCal

    ProbAbilistic CALculator - a package for computing with probability distributions

    Downloads: 0 This Week Last Update: See Project
  • Speech Research Tools

    Software for speech research. It includes programs and libraries for signal processing, along with general purpose scientific libraries. Most of the code is in Python, with C/C++ supporting code. Also, contains code releases corresponding to publishe

    Downloads: 0 This Week Last Update: See Project
  • Travel Market Simulator Icon

    Travel Market Simulator

    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.

    Downloads: 0 This Week Last Update: See Project
  • exome-cnv

    exome-cnv is an efficient, fast and robust tool for detection of CNVs in whole exome sequencing data based on Event-Wise testing (EWT) using read-depth of coverage.

    Downloads: 0 This Week Last Update: See Project
  • featureimpact Python package

    A Python package for estimating the statistical impact of features

    This package let's you compute the statistical impact of features given a scikit-learn estimator. The computation is based on the mean variation of the difference between quantile and original predictions. The impact is reliable for regressors and binary classifiers. Currently, all features must consist only of pure-numerical, non-categorical values.

    Downloads: 0 This Week Last Update: See Project
  • mediantracker

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

    Downloads: 0 This Week Last Update: See Project
  • mypypokergame

    Classic Texas Hold'Em Poker game in python.

    Downloads: 0 This Week Last Update: See Project
  • portas

    Pequeno script em Python para provar o problema de Monty Hall

    O jogo consiste no seguinte: Monty Hall (o apresentador) apresentava 3 portas aos concorrentes, sabendo que atrás de uma delas está um carro (prémio bom) e que as outras têm prêmios de pouco valor. Na 1ª etapa o concorrente escolhe uma porta (que ainda não é aberta); De seguida Monty abre uma das outras duas portas que o concorrente não escolheu, sabendo à partida que o carro não se encontra aí; Agora com duas portas apenas para escolher — pois uma delas já se viu, na 2ª etapa, que não tinha o prêmio — e sabendo que o carro está atrás de uma delas, o concorrente tem que se decidir se permanece com a porta que escolheu no início do jogo e abre-a ou se muda para a outra porta que ainda está fechada para então a abrir. Qual é a estratégia mais lógica? Ficar com a porta escolhida inicialmente ou mudar de porta? Com qual das duas portas ainda fechadas o concorrente tem mais probabilidades de ganhar? Por quê?

    Downloads: 0 This Week Last Update: See Project
  • python-asurv

    Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.

    Downloads: 0 This Week Last Update: See Project
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