Implements lasso and ridge regression for dichotomised outcomes (Rauschenberger et al. 2023, <doi:10.1080/02664763.2023.2233057>). Such outcomes are not naturally but artificially binary. They indicate whether an underlying measurement is greater than a threshold.

Provides 'coroutines' for R, a family of functions that can
    be suspended and resumed later on. This includes 'async' functions
    (which await) and generators (which yield). 'Async' functions are
    based on the concurrency framework of the 'promises' package.
    Generators are based on a dependency free iteration protocol defined
    in 'coro' and are compatible with iterators from the 'reticulate'
    package.

Contains an implementation of a confounding robust independent component analysis (ICA) for noisy and grouped data. The main function coroICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding based on user-specified groups. Additionally, the package contains the function uwedge() which can be used to approximately jointly diagonalize a list of matrices. For more details see the project website <https://sweichwald.de/coroICA/>.

Manipulate and view coronavirus data and other societally relevant data at a basic level.

Offers access to a database on government responses to the COVID-19 pandemic. 
    To date, the 'CoronaNet' dataset provides the most comprehensive and granular 
    documentation of such government policies in the world, capturing data for 
    20 broad policy categories alongside many other dimensions, including the 
    initiator, target, and timing of a policy. This package is a programmatic 
    front-end to up-to-date 'CoronaNet' policy records and the 'CoronaNet' policy intensity index scores. 
    For more information, see Cheng et al. (2020) <doi:10.1038/s41562-020-0909-7>.

Provides a daily summary of the Coronavirus (COVID-19) cases by state/province. Data source: Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus <https://systems.jhu.edu/research/public-health/ncov/>.