Perform a Bayesian estimation of the ordinal exploratory 
    Higher-order General Diagnostic Model (OHOEGDM) for Polytomous Data 
    described by Culpepper, S. A. and Balamuta, J. J. (In Press) <doi:10.1080/00273171.2021.1985949>.

Ordered homogeneity pursuit lasso (OHPL)
    algorithm for group variable selection proposed in Lin et al. (2017)
    <DOI:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the
    homogeneity structure in high-dimensional data and enjoys the
    grouping effect to select groups of important variables
    automatically. This feature makes it particularly useful for
    high-dimensional datasets with strongly correlated variables,
    such as spectroscopic data.

A client that grants access to the power of the 'ohsome API'
    from R. It lets you analyze the rich data source of the 
    'OpenStreetMap (OSM)' history. You can retrieve the geometry of 'OSM' 
    data at specific points in time, and you can get aggregated statistics 
    on the evolution of 'OSM' elements and specify your own temporal, 
    spatial and/or thematic filters.

Calculate's Tomoka Ohta's partitioning of linkage disequilibrium,
 deemed D-statistics, for pairs of loci. Petrowski et al. (2019) <doi:10.5334/jors.250>.

Facilitates the automatic detection of acoustic signals, 
    providing functions to diagnose and optimize the performance of detection 
    routines. Detections from other software can also be explored and optimized. 
    This package has been peer-reviewed by rOpenSci.
    Araya-Salas et al. (2022) <doi:10.1101/2022.12.13.520253>.

Provides simple crosstab output with optional statistics (e.g., Goodman-Kruskal Gamma, Somers' d, and Kendall's tau-b) as well as two-way and one-way tables. The package is used within the statistics component of the Masters of Science (MSc) in Social Science of the Internet at the Oxford Internet Institute (OII), University of Oxford, but the functions should be useful for general data analysis and especially for analysis of categorical and ordinal data.