Performs goodness of fits tests for both high and low-dimensional linear models.
    It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity.
    In addition one can test the significance of potentially large groups of variables, and also
    produce p-values for the significance of individual variables in high-dimensional linear
    regression.

Estimating repeatability (intra-class
    correlation) from Gaussian, binary, proportion and Poisson data.

The 'Public Trading API' <https://public.com/api/docs> allows clients to access their brokerage accounts,  request market data, and place stock/etf/option orders.

Client for accessing data journalism APIs from ProPublica <http://www.propublica.org/>.

An R interface to the Pushbullet messaging service which
 provides fast and efficient notifications (and file transfer) between
 computers, phones and tablets.  An account has to be registered at the 
 site <https://www.pushbullet.com> site to obtain a (free) API key.

Provides a classifier independent filter method for high-dimensional
    gene-expression feature selection. The Run Purity Weighted Nearest Shrunken
    Centroid ('RPWNSC') score ranks genes by multiplying a run based purity score,
    which measures the compactness of class labels after sorting samples by each
    feature, by a scaled nearest shrunken centroid score, which measures
    standardized class centroid separation relative to within class variation.
    The top ranked features can then be used with downstream classifiers without
    wrapper search, feature clustering, or classifier dependent training. 
    'Amjad Ali, Zardad Khan, Saeed Aldahmani' (2026) <doi:10.1016/j.mlwa.2026.100947>.

Provides portable access from 'R' to biomedical image processing toolbox 
    'ANTs' by Avants et al. (2009) <doi:10.54294/uvnhin> via seamless
    integration with the 'Python' implementation 'ANTsPy'. Allows biomedical 
    images to be processed in 'Python' and analyzed in 'R', and vice versa 
    via shared memory. See 'citation("rpyANTs")' for more reference information.