Showing 5 open source projects for "pca"

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    NAVAL-SEM

    NAVAL-SEM

    Award-winning open-source offline SEM platform for PLS-SEM & CB-SEM

    NAVAL-SEM is an award-winning, free and open-source offline Structural Equation Modeling (SEM) platform supporting PLS-SEM and CB-SEM workflows. Designed for researchers, PhD scholars, professors, and analysts, it provides visual model building, measurement assessment, structural model analysis, and reproducible research workflows without subscriptions or cloud dependency. Features include: • PLS-SEM & CB-SEM • Bootstrapping, mediation, moderation & conditional process analysis • HTMT,...
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    Downloads: 24 This Week
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  • 2
    Accord.NET Framework

    Accord.NET Framework

    Scientific computing, machine learning and computer vision for .NET

    The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
    Downloads: 1 This Week
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  • 3
    A Matlab software routine to perform Principal Component Analysis using Covariance, Correlation or Comedian as the criterion. Though, initially developed for experiments related to fretting wear but can be effectively used to interpret experimental data from any field. The attached files contain source code as well as a sample MATLAB (.mat) data file of 13 variables. It could be replaced to the data file of your choice. The code is open source but you are requested to give credits if used....
    Downloads: 0 This Week
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  • 4
    This project provides a Fortran90 library and a python module for singular spectrum analyses such as PCA/EOF or MSSA. It is intended for people interested, for example, in analysing climate or financial variability.
    Downloads: 0 This Week
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  • 5
    Source code for the paper J. Keiner and B. Waterhouse. Fast Principal Components Analysis method for finance problems with unequal time steps. In P. L'Ecuyer and A. B. Owen, editors, Monte Carlo and Quasi-Monte Carlo Methods 2008, Springer Verlag, 2010
    Downloads: 0 This Week
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