A likelihood method is implemented to present evidence for evaluating bioequivalence (BE). The functions use bioequivalence data [area under the blood concentration-time curve (AUC) and peak concentration (Cmax)] from various crossover designs commonly used in BE studies including a fully replicated, a partially replicated design, and a conventional 2x2 crossover design. They will calculate the profile likelihoods for the mean difference, total standard deviation ratio, and within subject standard deviation ratio for a test and a reference drug. A plot of a standardized profile likelihood can be generated along with the maximum likelihood estimate and likelihood intervals, which present evidence for bioequivalence. See Liping Du and Leena Choi (2015) <doi:10.1002/pst.1661>.

Bell regression models for count data with overdispersion. The implemented models account for ordinary and zero-inflated regression models under both frequentist and Bayesian approaches. Theoretical details regarding the models implemented in the package can be found in Castellares et al. (2018) <doi:10.1016/j.apm.2017.12.014> and Lemonte et al. (2020) <doi:10.1080/02664763.2019.1636940>.

Tools to accurately benchmark and analyze execution times for
    R expressions.

Full implementation of the 28 distributions introduced as benchmarks for nonparametric density estimation by Berlinet and Devroye (1994) <https://hal.science/hal-03659919>. Includes densities, cdfs, quantile functions and generators for samples as well as additional information on features of the densities. Also contains the 4 histogram densities used in Rozenholc/Mildenberger/Gather (2010) <doi:10.1016/j.csda.2010.04.021>.

Methods for frontier
    analysis, Data Envelopment Analysis (DEA), under different
    technology assumptions (fdh, vrs, drs, crs, irs, add/frh, and fdh+),
    and using different efficiency measures (input based, output based,
    hyperbolic graph, additive, super, and directional efficiency). Peers
    and slacks are available, partial price information can be included,
    and optimal cost, revenue and profit can be calculated. Evaluation of
    mergers is also supported.  Methods for graphing the technology sets
    are also included. There is also support for comparative methods based
    on Stochastic Frontier Analyses (SFA) and for convex nonparametric 
    least squares of convex functions (STONED). In general, the methods 
    can be used to solve not only standard models, but also many other 
    model variants. It complements the book, Bogetoft and Otto,
    Benchmarking with DEA, SFA, and R, Springer-Verlag, 2011, but can of
    course also be used as a stand-alone package.