A standardized user interface for column selection, that
    facilitates dataset merging in 'teal' framework.

Collection of 'shiny' widgets to support 'teal' applications.
    Enables the manipulation of application layout and plot or table
    settings.

Provides color palettes corresponding to professional and amateur, 
    sports teams. These can be useful in creating data graphics that are themed 
    for particular teams.

Models the direction of the maximum horizontal stress using
    relative plate motion parameters. Statistical algorithms to evaluate
    the modeling results compared with the observed data. Provides plots
    to visualize the results. Methods described in Stephan et al. (2023)
    <doi:10.1038/s41598-023-42433-2> and Wdowinski (1998)
    <doi:10.1016/S0079-1946(98)00091-3>.

The typicality and eccentricity data analysis (TEDA) framework was
    put forward by Angelov (2013) <DOI:10.14313/JAMRIS_2-2014/16>. It has been further developed into multiple
    different techniques since, and provides a non-parametric way of determining how
    similar an observation, from a process that is not purely random, is to other
    observations generated by the process. This package provides code to use the
    batch and recursive TEDA methods that have been published.

Inferring causation from time series data through empirical dynamic modeling (EDM), with methods such as convergent cross mapping from Sugihara et al. (2012) <doi:10.1126/science.1227079>, partial cross mapping as outlined in Leng et al. (2020) <doi:10.1038/s41467-020-16238-0>, and cross mapping cardinality as described in Tao et al. (2023) <doi:10.1016/j.fmre.2023.01.007>.

Implements methods to fit Virtual Twins models (Foster et al. 
  (2011) <doi:10.1002/sim.4322>) for identifying subgroups with differential
  effects in the context of clinical trials while controlling the probability
  of falsely detecting a differential effect when the conditional average
  treatment effect is uniform across the study population using parameter
  selection methods proposed in Wolf et al. (2022) 
  <doi:10.1177/17407745221095855>.