Fully-interactive R interface to the 'OpenBUGS' software for Bayesian analysis using MCMC sampling.  Runs natively and stably in 32-bit R under Windows.  Versions running on x86Linux and on 64-bit R under Windows are in "beta" status and less efficient.

Provides high-level modeling functions to define and train
    models using the 'torch' R package. Models include linear, logistic,
    and multinomial regression as well as multilayer perceptrons.

Provides the functions for Brunner-Munzel test and
    permuted Brunner-Munzel test,
    which enable to use formula, matrix, and table as argument.
    These functions are based on Brunner and Munzel (2000)
     <doi:10.1002/(SICI)1521-4036(200001)42:1%3C17::AID-BIMJ17%3E3.0.CO;2-U>
    and Neubert and Brunner (2007) <doi:10.1016/j.csda.2006.05.024>,
    and are written with FORTRAN.

Provide real-time access to data from the Regional Securities Exchange SA(<https://www.brvm.org/en>), commonly known as the 'BRVM' stock exchange. The goal is to facilitate data access for users of the R programming language. The package includes a variety of data that can be accessed by calling functions.

When samples contain missing data, are small, or are suspected of bias,
    estimation of scale reliability may not be trustworthy.  A recommended solution
    for this common problem has been Bayesian model estimation.  Bayesian methods
    rely on user specified information from historical data or researcher intuition 
    to more accurately estimate the parameters.  This package provides a user friendly
    interface for estimating test reliability.  Here, reliability is modeled as a beta
    distributed random variable with shape parameters alpha=true score variance and
    beta=error variance (Tanzer & Harlow, 2020) <doi:10.1080/00273171.2020.1854082>.

Allows the user to generate bootstrap cards within
    R markdown documents. Intended for use in conjunction with
    R markdown HTML outputs and other formats that support the 
    bootstrap 4 library.