Anscombe's quartet are a set of four two-variable datasets that 
    have several common summary statistics but which have very different joint 
    distributions.  This becomes apparent when the data are plotted, which 
    illustrates the importance of using graphical displays in Statistics.  This
    package enables the creation of datasets that have identical marginal sample
    means and sample variances, sample correlation, least squares regression 
    coefficients and coefficient of determination.  The user supplies an initial 
    dataset, which is shifted, scaled and rotated in order to achieve target 
    summary statistics.  The general shape of the initial dataset is retained. 
    The target statistics can be supplied directly or calculated based on a 
    user-supplied dataset.  The 'datasauRus' package 
    <https://cran.r-project.org/package=datasauRus> provides further examples 
    of datasets that have markedly different scatter plots but share many 
    sample summary statistics.

Machine learning based package to predict anti-angiogenic peptides using heterogeneous sequence descriptors. 'AntAngioCOOL' exploits five descriptor types of a peptide of interest to do prediction including: pseudo amino acid composition, k-mer composition, k-mer composition (reduced alphabet), physico-chemical profile and atomic profile. According to the obtained results, 'AntAngioCOOL' reached to a satisfactory performance in anti-angiogenic peptide prediction on a benchmark non-redundant independent test dataset.

Edit an 'Antares' simulation before running it : create new areas, links, thermal
    clusters or binding constraints or edit existing ones. Update 'Antares' general & optimization settings.
    'Antares' is an open source power system generator, more information available here : <https://antares-simulator.org/>.

Process results generated by 'Antares', a powerful open source software developed by
    RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about
    'Antares' here: <https://github.com/AntaresSimulatorTeam/Antares_Simulator>).
    This package provides functions to create new columns like net load, load factors, upward and
    downward margins or to compute aggregated statistics like economic surpluses
    of consumers, producers and sectors.