Showing 5 open source projects for "simple software manager"

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  • 1
    NAVAL-SEM

    NAVAL-SEM

    Free offline SEM software with HTMT, bootstrapping & exports

    NAVAL-SEM is a free, open-source, fully offline desktop application for Structural Equation Modeling (SEM), supporting both PLS-SEM and CB-SEM workflows. Designed for researchers, PhD scholars, professors, students, and analysts, it enables advanced quantitative research without subscriptions, cloud dependencies, or proprietary software restrictions. Key features include visual drag-and-drop model building, bootstrapping, mediation analysis, HTMT, AVE, Composite Reliability (CR),...
    Downloads: 27 This Week
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  • 2
    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
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  • 3
    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: 0 This Week
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  • 4

    CoLabR

    A simple user interface to the R software environment.

    A simple user interface to the R software environment. It is designed for people new to R and provides the user with easy access to their variables and data along with pointers to the most basic commands. It also allows for multiple people to share data across different sessions on different machines. In this way it also offers a collaborative environment for people to work together in remote locations.
    Downloads: 0 This Week
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  • 5

    dAnalytics

    dAnalytics is a software made for education in discriminant analysis.

    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.
    Downloads: 0 This Week
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