Analyzes and modifies metabolomics raw data (generated using 
    Gas Chromatography-Atmospheric Pressure Chemical Ionization-Mass Spectrometry) 
    to correct overloaded signals, i.e. ion intensities exceeding detector 
    saturation leading to a cut-off peak. Data in 'xcmsRaw' format are 
    accepted as input and 'mzXML' files can be processed alternatively. 
    Overloaded signals are detected automatically and modified using an Gaussian 
    or an Isotopic-Ratio approach. Quality control plots are generated and 
    corrected data are stored within the original 'xcmsRaw' or 'mzXML' 
    respectively to allow further processing.

Calculate a set of corrected test statistics for cases when samples
    are not independent, such as when classification accuracy values are obtained
    over resamples or through k-fold cross-validation, as proposed by Nadeau and Bengio (2003) <doi:10.1023/A:1024068626366> 
    and presented in Bouckaert and Frank (2004) <doi:10.1007/978-3-540-24775-3_3>.

Reads 'Word' documents containing incomplete bibliographic references and 
    produces an updated file with standardized and complete references. The package 
    provides functions to retrieve missing authors, titles, journal details, volume, 
    issue, and page numbers. Digital object identifiers (DOIs) are retrieved using the 
    'CrossRef' application programming interface (API) <https://api.crossref.org>, and 
    references are formatted following DOI-based citation standards as described by 
    Paskin (2010) <doi:10.1000/182> and the 'citation.doi.org' service 
    <https://citation.doi.org>. The package is intended to simplify reference preparation 
    for scientific journal submissions.

Helps visualizing what is summarized in Pearson's correlation coefficient. That is, it visualizes its main constituent, namely the distances of the single values to their respective mean. The visualization thereby shows what the etymology of the word correlation contains: In pairwise combination, bringing back (see package Vignette for more details). I hope that the 'correlatio' package may benefit some people in understanding and critically evaluating what Pearson's correlation coefficient summarizes in a single number, i.e., to what degree and why Pearson's correlation coefficient may (or may not) be warranted as a measure of association.