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.

Make 'Bootstrap 4' Shiny dashboards. Use the full power
    of 'AdminLTE3', a dashboard template built on top of 'Bootstrap 4' 
    <https://github.com/ColorlibHQ/AdminLTE>.

Collection of functions, data sets and code examples 
 for evaluations of field trials with the objective of equivalence assessment.

Tools to fit Bayesian state-space models to animal tracking data. Models are provided for location 
    filtering, location filtering and behavioural state estimation, and their hierarchical versions. 
    The models are primarily intended for fitting to ARGOS satellite tracking data but options exist to fit 
    to other tracking data types. For Global Positioning System data, consider the 'moveHMM' package. 
    Simplified Markov Chain Monte Carlo convergence diagnostic plotting is provided but users are encouraged 
    to explore tools available in packages such as 'coda' and 'boa'.