Showing 10 open source projects for "statistical analysis"

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  • 1
    HEALPix

    HEALPix

    Data Analysis, Simulations and Visualization on the Sphere

    Software for pixelization, hierarchical indexation, synthesis, analysis, and visualization of data on the sphere. Please acknowledge HEALPix by quoting the web page http://healpix.sourceforge.net (or https://healpix.sourceforge.io) and publication: K.M. Gorski et al., 2005, Ap.J., 622, p.759 Full software documentation available at https://healpix.sourceforge.io/documentation.php Wiki Pages: https://sourceforge.net/p/healpix/wiki/Home Exchanging Data with HEALPix (in FITS files):...
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    Downloads: 1,144 This Week
    Last Update:
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  • 2
    DataMelt

    DataMelt

    Computation and Visualization environment

    DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. ...
    Downloads: 9 This Week
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  • 3
    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit for All of Us

    DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. ...
    Downloads: 0 This Week
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  • 4
    PMM-Lab

    PMM-Lab

    Predictive Microbial Modeling plug-in for KNIME

    ...It consists of three components: • a library of KNIME nodes (called PMM-Lab), • a library of “standard” workflows • an HSQL database.to store experimental data and microbial models. Altogether these components are designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models (PMM). Users can apply PMM-Lab to proprietary or public data and create bacterial growth / survival / inactivation models. The framework can easily be extended to other model types, e.g. growth/no-growth boundary models. PMM-Lab has been initiated and provided by the Federal Institute for Risk Assessment - BfR (Berlin, Germany). ...
    Downloads: 1 This Week
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  • 5

    Ship Lock Scheduling

    Scheduling lockages at ship locks with several parallel lock chambers

    This Java software includes algorithms of combinatorical optimization for the NP-hard offline ship lock scheduling problem. Solutions and performed computations can be displayed graphically. Besides, there is a framework for generating test instances and running these in parallel, as well as R/JGR code for statistical evaluation. Some tools for estimating the quality of calculated solutions will be further improved. Initially the software was developed within a project of TU Berlin regarding...
    Downloads: 0 This Week
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  • 6

    SCaVis

    Scientific Computation and Visualization Environment

    SCaVis is an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. SCaVis can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. ...
    Downloads: 2 This Week
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  • 7

    iMir

    Integrated pipeline for HT miRNA-Seq data analysis

    Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular pipeline, called iMir, integrating multiple open source modules and resource in an automated workflow, devising different statistical approaches to analyze data rigorously. iMir comprises also a Graphical User Interface (GUI), so that the pipeline is particularly suited for biologist and early stage bioinformaticians and produces both graphics and text outputs.
    Downloads: 0 This Week
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  • 8
    CoDaPack
    Compositional data analysis, following the approach introduced by John Aitchison, is not straightforward to use with standard statistical packages. CoDaPack provides a software capable of using the Aitchison methodology.
    Downloads: 0 This Week
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  • 9
    jHepWork

    jHepWork

    jHepWork was a name of the DataMelt program in 2005-20013

    jHepWork (2005-2013) was an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with the Jython (Python) scripting language. Currently the project is known under the name DataMelt (https://datamelt.org)
    Downloads: 0 This Week
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  • 10
    JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
    Downloads: 0 This Week
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