Provides a framework for the measurement and partitioning of
    the (similarity-sensitive) biodiversity of a metacommunity and its
    constituent subcommunities. Richard Reeve, et al. (2016)
    <doi:10.48550/arXiv.1404.6520>.

A task-oriented R interface to the 'RDKit' <https://www.rdkit.org>
    library through its 'Python' API via 'reticulate'. The package offers
    high-level cheminformatics functionality, including molecule parsing,
    descriptor calculation, and fingerprint generation without replicating the 
    native structure of 'RDKit'.

Implements safe policy learning under regression discontinuity designs
    with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>.
    The learned cutoffs are guaranteed  to perform no worse than the existing
    cutoffs in terms of overall outcomes. The 'rdlearn' package also includes
    features for visualizing the learned cutoffs relative to the baseline and
    conducting sensitivity analyses.

Provides tools to perform randomization inference for RD designs under local randomization: rdrandinf() to perform hypothesis testing using randomization inference, rdwinselect() to select a window around the cutoff in which randomization is likely to hold, rdsensitivity() to assess the sensitivity of the results to different window lengths and null hypotheses and rdrbounds() to construct Rosenbaum bounds for sensitivity to unobserved confounders. See Cattaneo, Titiunik and Vazquez-Bare (2016) <https://rdpackages.github.io/references/Cattaneo-Titiunik-VazquezBare_2016_Stata.pdf> for further methodological details, and references.

Estimates the rearranged dependence measure ('RDM') of two continuous random variables for different underlying measures. 
  Furthermore, it provides a method to estimate the (SI)-rearrangement copula using empirical checkerboard copulas.
  It is based on the theoretical results presented in Strothmann et al. (2022) <arXiv:2201.03329> and Strothmann (2021) <doi:10.17877/DE290R-22733>.