It implements the Nelson-Siegel and the Nelson-Siegel-Svensson
	term structures.

Wrapper functions around the Facebook Marketing 'API' to create,
    read, update and delete custom audiences, images, campaigns, ad sets, ads and
    related content.

Implements a very fast C++ algorithm to quickly bootstrap receiver
    operating characteristics (ROC) curves and derived performance metrics,
    including the area under the curve (AUC) and the partial area under the curve as well as 
    the true and false positive rate. The analysis of paired receiver operating curves is supported as well,
    so that a comparison of two predictors is possible. You can also plot the
    results and calculate confidence intervals. On a typical desktop computer the time needed for 
    the calculation of 100000 bootstrap replicates given 500 observations requires time on the
    order of magnitude of one second.

Provides access to a range of functions for computing and visualizing the Full Bayesian Significance Test (FBST) and the e-value for testing a sharp hypothesis against its alternative, and the Full Bayesian Evidence Test (FBET) and the (generalized) Bayesian evidence value for testing a composite (or interval) hypothesis against its alternative. The methods are widely applicable as long as a posterior MCMC sample is available.

Provides a streamlined, standard evaluation-based approach to multivariate function composition. Allows for chaining commands via a forward-pipe operator, %>%.

Perform various floating catchment area methods to calculate a
    spatial accessibility index (SPAI) for demand point data. The distance
    matrix used for weighting is normalized in a preprocessing step using
    common functions (gaussian, gravity, exponential or logistic).

Provides tools to perform fuzzy formal concept
    analysis, presented in Wille (1982) <doi:10.1007/978-3-642-01815-2_23>
    and in Ganter and Obiedkov (2016) <doi:10.1007/978-3-662-49291-8>.  It
    provides functions to load and save a formal context, extract its
    concept lattice and implications.  In addition, one can use the
    implications to compute semantic closures of fuzzy sets and, thus,
    build recommendation systems.