Search Results for "java open source" - Page 2

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!

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

Collection of utilities based on two basics classes: Matematica and VarData. Matematica) performs math operations on vectors and matrices for smoothing, interpolation, convolution, image processing... VarData) manipulate a structure of points connected by links. Addraw) openGL engine. ElPoly) analyze mechanical properties of polymer and membrane like structures. Addyn) perform molecular dynamics and Monte Carlo simulations and has a solver for 4th oder PDE. Avvis) perform all the...

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).

dAnalytics is a software made for educational purposes to work with discriminant analysis. It's a very simple calculator over bi-dimensional populations. You input a file with two columns (one for each variable) and tryout different separations of populations (blue and red) and analyze it's efficiency by observing the eigen value result for the attempted separation. It also gives many information about the statistics both of the input and the separated populations. There's a documentation...

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.

Free and open source standalone program capable of conducting between, within, and mixed analyses of variance (ANOVA). Provides a simple graphical user interface for specifying analyses and interaction plots (analyses performed by http://code.google.com/p/pyvttbl/). Features: - Capable of high order factorial designs (> 2 factors) - Within and mixed analyses of variance provide corrections for violations of sphericity (Huynh-Feldt, Greenhouse-Geisser, Box) - A variety of data transformations can be applied (log10, reciprocal, arcsine, square-root, and Windsor) - Generalized eta-squared measures of effect size - Post-hoc power analysis (should match G*Power) - Outputs include tables of estimated marginal means - Up to 4-way interaction plots with errorbars (png, svg) - Confidence intervals account for within-subject variability (where applicable; Loftus and Masson, 1994) - Non-proprietary HTML output files - Non-proprietary codebase Gotchas: - Assumes balanced designs

HMMLab is a Hidden Markov Model editor oriented on HMMs for speach recognition. It can create, edit, train and visualize HMMs. HMMLab supports loading/saving HMMs from/to HTK files.

mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.

This program was written to dimonstrate errors in transmission for a presentation on Claude Shannon's Noisy Channel Coding Theorem. It takes an input file, the probability of a bit being flipped, and, if specified, the size of the header of the file. The program was intended to take monochrome bitmap files as input, so that each bit refers to a pixel in the image and thus, it would be easy to see errors in the output file, as some of the pixels would be flipped; however, it will work on any...

This project examines techniques to model three-dimensional rigid body motion using the geometric algebra of Dual Quaternions and how such models compare to more traditional models when used in underconstrained filtering applications.

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.

Worst Cases is a python script that enables calculations on worst case objects. Like a calculator operating on worst cases (e.g. [1,2,3]) rather than on real numbers (2.35) WARNING: This program is released as is, and has never been extensively teste

Measurement uncertainties with Python.

snlanalytic is a small Python script that takes a stem-and-leaf plot as input and returns basic statistics (sum, mean, median, mode) to the user.

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.

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.

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

A small simulator for Mendelian genetics, genetic drift, natural selection and random mutations, built on matplotlib and wxpython. A graph will be generated that traces the distribution of genotypes at successive generations.

PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.

Classic Texas Hold'Em Poker game in python.

PYthon RELiabilitY A python package implementing state-of-the-art numerical methods arising in the field of uncertainty quantification : from statistical inference to uncertainty propagation for various purposes.

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,...