Open Source Linux Statistics Software - Page 8
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Statistics Software for Linux
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The Time2 Java library provides generic time series with configurable time domains.
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TimescapeGlobal
a space-time interpolation geostatistical tool
This software is a time-aware geostatistical tool. Including time variability adds further issues to the already complicated field of geostatistical interpolation. On the other hand, most of the distributions of variables used in Earth and environmental sciences show patterns of change over time, not only in space. This tool is a free, open-source software, based on a generalization of the Inverse Distance Weighted algorithm. It outputs three-dimensional, layered discrete models from which time series and equal-time GIS Grid layers can be extracted. -
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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.
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us. -
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VBS for Research on the Internet
Welcome to the Volunteer-Based System for Research on the Internet!
Welcome to the Volunteer-Based System for Research on the Internet! This system is designed to provide detail data about applications used in the Internet. This information can be used for: - obtaining the knowledge which applications are most frequently used in the network - providing the users some basic statistics about their Internet connection usage (for example for which kinds of applications their connection is used the most) - creating scientific profiles of traffic generated by different applications or different groups of applications - creating a traffic generator, to imitate traffic generated by particular applications, or to imitate the real traffic in the network - implementing smart assessment of QoS in the network at the users' level and in the core of the network - obtaining precise data needed to train Machine Learning Algorithms - many more cases :-) -
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Statistical program, somewhat like shareware DataFit. You may provide a custom template (or exchange the template library with your friends or Internet including sf.net) and test your tabled data. Calculates F-ratio.
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Yet Another Data Mining Platform
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Vytics Community
Query and plot data in seconds (Excel, CSV, SQL and NoSQL DBMS)
Vytics lets you query and plot csv data, Excel files, databases (SQL and NoSQL). You can also organize your queries, data and graphs into reports and projects. -
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Weibull-based reliability toolkit for R
R package for Weibull analysis on (life-)time observations.
This is a small R package for doing Weibull-based reliability analysis. This R package is now obsolete and has been superseded by 'project Abernethy' on http://r-forge.r-project.org/projects/abernethy/. -
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Yaşını Bul
A program to find your age
Yaşını Bul is a program to find your age with day, month and year enterence today and born date. -
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abc-sde
approximate Bayesian computation for stochastic differential equations
A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/ -
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allink
Software for data analysis, image processing, simulations, solver.
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 operation of Matematica on different sets of data visualized on a Qt graphical interface. DrImage) image manipulation on the Matematica filters. The program is intended to use as less as possible external libs (optional: openGL, gsl, fftw, cgal, png, tiff, boost, MPI, Qt...). -
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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.
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coalescent
Software tool for Research in Computational Population Genetics
Development of exact and approximate methods (Importance Sampling and MCMC based) for computing likelihoods under the standard population genetic models of mutation,migration & recombination. Project issues are mainatined at https://freecode4susant.atlassian.net/browse/COALESCENT -
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covid19-de-stats
Statistiken zu COVID-19 in Deutschland
Tägliche Statistiken und zugehörige Programme zur Darstellung der Verbreitung von COVID-19 in Deutschland. -
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ctsa
A Univariate Time Series Analysis package in ANSI C
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 -
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datadensityplot
Creates a data density plot of a 2 dimensional data distribution.
Shows the data density of a 2 dimensional distribution. The problem of showing data density visually is not mathematically well defined, and there are several methods. The program uses sum of reciprocal squared distance to calculate density at each point, with a smear factor to prevent points going to infinity. The smear factor also controls the amount of clustering. There are several options for colour output. Input is via a csv (comma-separated values) file. Now there's a nice GUI built in Baby X for Linux and Windows -
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The final build of this software now is distributed in R, embedded in "RedeR': an R/Bioconductor package for hierarchical and nested network analysis... more about RedeR: http://bioconductor.org/packages/2.9/bioc/html/RedeR.html
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fantail-mlkit
The fantail machine learning toolkit (Moved)
Moved to https://github.com/quansun/fantail-ml -
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fesslix
Stochastic Analysis
A brief summary of the main features of Fesslix: - Perform non-intrusive reliability analysis or Bayesian updating either --- by running commands on the command line or --- by means of an Octave interface or --- by means of a Python interface - Flexible input language for writing Fesslix parameter files --- Control flow statements (e.g. if, for, while) --- Most parameters can be defined as functions - Working with response surfaces - Linear finite element analysis using truss, beam and plane stress/strain elements - Spectral Stochastic Finite Elements - Bayesian networks This is the download page for Windows executables of Fesslix. -
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A software framework to build maps for Neurospora crassa genome based on probabilistic models of meiotic recombination. A netbeans platform application is built to incorporate the computations. Project issues are mainatined at https://freecode4susant.atlassian.net/browse/GENOMEMAP
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gsasnp2
PubMed ID: 29562348 / DOI: 10.1093/nar/gky175
* GSA-SNP2 is a successor of GSA-SNP (Nam et al. 2010, NAR web server issue). GSA-SNP2 accepts human GWAS summary data (rs numbers, p-values) or gene-wise p-values and outputs pathway genesets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways. * Article: SYoon, HCTNguyen, YJYoo, JKim, BBaik, SKim, JKim, SKim, DNam, "Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2", Nucleic Acids Research, Vol. 46(10), e60(2018). * PubMed ID: 29562348 * DOI: 10.1093/nar/gky175 -> PLEASE MOVE OR MAKE A COPY OF 'DATA' FOLDER INTO YOUR INTENSIVE TEST FOLDER (I.E. LINUX, MAC OR WINDOWS SPECIFIED FOLDER) TO ALLOW THE PROGRAM TO FIND THE PREDESIGNED DATA. * UPDATE NOTE: -> Sep-1-2020: add an update for Ubuntu-20.04. You will need Boost library installed (sudo apt-get install libboost-all-dev) -> Mar-7-2018: revise header terms in the output file -
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hSDM
R package for hierarchical species distribution models
hSDM is an R package for hierarchical species distribution models. Such models allows interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results. -
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hbgm
'Hierarchical Bond Graph Modelling of Biochemical Networks'
Scripts and supplementary data for the manuscript 'Hierarchical Bond Graph Modelling of Biochemical Networks': Peter J. Gawthrop(1), Joseph Cursons(1,2), and Edmund J. Crampin(1-4). (1) Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia. (2) ARC Centre of Excellence in Convergent Bio-Nano Science, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia. (3) Department of Mathematics and Statistics, University of Melbourne, Victoria 3010, Australia. (4) School of Medicine, University of Melbourne, Victoria 3010, Australia Draft paper available at http://arxiv.org/abs/1503.01814
