Showing 6 open source projects for "statistical analysis"

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  • 1
    GrainSizeTools script

    GrainSizeTools script

    A Python script for estimating the grain size from thin sections

    Homepage & docs: http://marcoalopez.github.io/GrainSizeTools/ GrainSizeTools is a free, open-source, cross-platform script written in Python that provides several tools for (1) estimating average grain size in polycrystalline materials, (2) characterizing the nature of the distribution of grain sizes (either from apparent distributions or approximating 3D grain size distributions via stereology), and estimating differential stress via paleopizometers. The script requires as the input the...
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  • 2
    Geophysical Library is a C++-library to handle geophysical data. At the moment the focus is on magnetotelluric and seismic data. It also includes a genetic algorithm for data inversion, signal processing and statistics routines.
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  • 3
    GPS Interactive Time Series Analysis

    GPS Interactive Time Series Analysis

    A software for processing and analyzing time series in Earth Science

    Along with calculating basic statistics and quality parameters such as mean and variance, the soft-ware is capable of importing and visualizing different standard time series formats, determining and removing jumps and outliers, and makes numerical and publication quality graphical outputs. Bivariate statistical analysis (including correlation coefficient and linear regression) and time series analysis (including auto and cross-spectral analysis, wavelet power spectrum, spectrogram and periodicities) form the main analysis features of the software.
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  • 4
    SediStat is simple command line aplication for automatization of statistical calculations used in facial analysis of deep water sediments. In actual version are incorporated methods of R/S analysis and Markov chains computations.
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  • 5
    CHAC is a MATLAB toolbox for statistical downscaling.
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  • 6
    PySDB is simple to use field data manager for structural geologists written in Python. Data are traditionally organized by sites and rock units, classified by structural types and could be freely tagged by user-defined labels.
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