Contains functions for evaluating, analyzing, and fitting combined
    action dose response surfaces with the Bivariate Response to Additive
    Interacting Doses (BRAID) model of combined action, along with tools for
    implementing other combination analysis methods, including Bliss independence,
    combination index, and additional response surface methods.

Deals with the braid groups. Includes creation of some
    specific braids, group operations, free reduction, and Bronfman
    polynomials. Braid theory has applications in fluid mechanics and
    quantum physics. The code is adapted from the 'Haskell' library
    'combinat', and is based on Birman and Brendle (2005)
    <doi:10.48550/arXiv.math/0409205>.

Blind users do not have access to the graphical output from R
    without printing the content of graphics windows to an embosser of
    some kind. This is not as immediate as is required for efficient
    access to statistical output.  The functions here are created so that
    blind people can make even better use of R. This includes the text
    descriptions of graphs, convenience functions to replace the
    functionality offered in many GUI front ends, and experimental
    functionality for optimising graphical content to prepare it for
    embossing as tactile images.

A statistical tool to inference the multi-level partial correlations based on multi-subject time series data, especially for brain functional connectivity. It combines both individual and population level inference by using  the methods of Qiu and Zhou. (2021)<DOI: 10.1080/01621459.2021.1917417> and Genovese and Wasserman. (2006)<DOI: 10.1198/016214506000000339>. It realizes two reliable estimation methods of partial correlation coefficients, using scaled lasso and lasso. It can be used to estimate individual- or population-level partial correlations, identify nonzero ones, and find out unequal partial correlation coefficients between two populations.

A set of tools for performing graph theory analysis of brain MRI
    data. It works with data from a Freesurfer analysis (cortical thickness,
    volumes, local gyrification index, surface area), diffusion tensor
    tractography data (e.g., from FSL) and resting-state fMRI data (e.g., from
    DPABI). It contains a graphical user interface for graph visualization and
    data exploration, along with several functions for generating useful
    figures.