Functions to perform maximum likelihood estimation, model-based clustering, discriminant and regression analysis with a circular response variable. <doi:10.1080/01621459.2019.1585249>.

Wraps the 'CIRCE' (<https://github.com/ohdsi/circe-be>) 'Java'
  library allowing cohort definition expressions to be edited and converted to 
  'Markdown' or 'SQL'.

Light-weight functions for computing descriptive statistics in different circular spaces (e.g., 2pi, 180, or 360 degrees), to handle angle-dependent biases, pad circular data, and more. Specifically aimed for psychologists and neuroscientists analyzing circular data. Basic methods are based on Jammalamadaka and SenGupta (2001) <doi:10.1142/4031>, removal of cardinal biases is based on the approach introduced in van Bergen, Ma, Pratte, & Jehee (2015) <doi:10.1038/nn.4150> and Chetverikov and Jehee (2023) <doi:10.1038/s41467-023-43251-w>.

Tools for interacting with the 'Circle CI' API
    (<https://circleci.com/docs/api/v2/>). Besides executing common tasks
    such as querying build logs and restarting builds, this package also
    helps setting up permissions to deploy from builds.

Draws circular "correlation wheel" plots in R, straight from a data frame of one
    row per observation. Variables are arranged around a circle, grouped and
    colour-tiled by category, and connected by curved links whose colour maps
    to the correlation coefficient, computed via a thin wrapper around
    corr.test() from the 'psych' package. Non-significant, weak, and
    within-category correlations can be masked. Categories, colours, and
    labels are all user-configurable.

Contains the adaptation of bubblebath from 'MATLAB', developed by Adam Danz and available through the 'MATLAB' Central File Exchange,
     and the tools to transform a dataframe of radii and points to plot-able paths.

Implementation of Librino, Levorato, and Zorzi (2014) <doi:10.1002/wcm.2305>
    algorithm for computation of the intersection areas of an arbitrary number of circles.