'DataSHIELD' is an infrastructure and series of R packages that 
    enables the remote and 'non-disclosive' analysis of sensitive research data.
    This package is the 'DataSHIELD' interface implementation for 'Opal', which is
    the data integration application for biobanks by 'OBiBa'. Participant data, once
    collected from any data source, must be integrated and stored in a central
    data repository under a uniform model. 'Opal' is such a central repository.
    It can import, process, validate, query, analyze, report, and export data.
    'Opal' is the reference implementation of the 'DataSHIELD' infrastructure.

Test for no adverse shift in two-sample comparison when we
    have a training set, the reference distribution, and a test set. The
    approach is flexible and relies on a robust and powerful test
    statistic, the weighted AUC. Technical details are in Kamulete, V. M.
    (2021) <arXiv:1908.04000>. Modern notions of outlyingness such as
    trust scores and prediction uncertainty can be used as the underlying
    scores for example.

You can retrieve 'Spotify' API Information such as artists, albums, tracks, features tracks, recommendations or related artists.
    This package allows you to search all the information by name and also includes a distance based algorithm to find similar songs.
	More information: <https://developer.spotify.com/documentation/web-api/> .

Perform a test of a simple null hypothesis about a 
    directly standardized rate and obtain the matching confidence 
    interval using a choice of methods.

The purpose of this package is to provide a comprehensive
    R interface to the Decision Support System for Agrotechnology
    Transfer Cropping Systems Model (DSSAT-CSM; see <https://dssat.net> for more information).
    The package provides cross-platform functions to read and
    write input files, run DSSAT-CSM, and read output files.

Creates survey designs for distance sampling surveys. These
    designs can be assessed for various effort and coverage statistics.
    Once the user is satisfied with the design characteristics they can 
    generate a set of transects to use in their distance sampling survey.
    Many of the designs implemented in this R package were first made 
    available in our 'Distance' for Windows software and are detailed in 
    Chapter 7 of Advanced Distance Sampling, Buckland et. al. (2008, 
    ISBN-13: 978-0199225873). Find out more about estimating animal/plant 
    abundance with distance sampling at <http://distancesampling.org/>.