An implementation of the Uniform Manifold Approximation and
    Projection dimensionality reduction by McInnes et al. (2018)
    <doi:10.48550/arXiv.1802.03426>. It also provides means to transform new data and
    to carry out supervised dimensionality reduction. An implementation of
    the related LargeVis method of Tang et al. (2016) <doi:10.48550/arXiv.1602.00370>
    is also provided. This is a complete re-implementation in R (and C++,
    via the 'Rcpp' package): no Python installation is required. See the
    uwot website (<https://github.com/jlmelville/uwot>) for more
    documentation and examples.

Provides convenience functions for user experience research
    with an emphasis on quantitative user experience testing and reporting.
    The functions are designed to translate statistical approaches to 
    applied user experience research.

An R interface to V8 <https://v8.dev>: Google's open source JavaScript
    and WebAssembly engine. This package can be compiled either with V8 version 6 
    and up or NodeJS when built as a shared library.

Various semiparametric and nonparametric statistical tools for
    immune correlates analysis of vaccine clinical trial data. This includes
    calculation of summary statistics and estimation of risk, vaccine efficacy,
    controlled effects (controlled risk and controlled vaccine efficacy), and
    mediation effects (natural direct effect, natural indirect effect,
    proportion mediated). See Gilbert P, Fong Y, Kenny A, and Carone, M (2022)
    <doi:10.1093/biostatistics/kxac024> and Fay MP and Follmann DA (2023)
    <doi:10.48550/arXiv.2208.06465>.

A method to visualize pharmacometric analyses which are impacted by
    covariate effects. Variability-aligned covariate harmonized-effects
    and time-transformation equivalent ('vachette') facilitates intuitive
    overlays of data and model predictions, allowing for comprehensive
    comparison without dilution effects. 'vachette' improves upon previous
    methods Lommerse et al. (2021) <doi:10.1002/psp4.12679>, enabling its
    application to all pharmacometric models and enhancing Visual Predictive
    Checks (VPC) by integrating data into cohesive plots that can highlight
    model misspecification.