Tools to create and manipulate probability distributions
    using S3.  Generics pdf(), cdf(), quantile(), and random() provide
    replacements for base R's d/p/q/r style functions.  Functions and
    arguments have been named carefully to minimize confusion for students
    in intro stats courses. The documentation for each distribution
    contains detailed mathematical notes.

A library of density, distribution function, quantile function, (bounded) raw moments and random generation for a collection of distributions relevant for the firm size literature. Additionally, the package contains tools to fit these distributions using maximum likelihood and evaluate these distributions based on (i) log-likelihood ratio and (ii) deviations between the empirical and parametrically implied moments of the distributions. We add flexibility by allowing the considered distributions to be combined into piecewise composite or finite mixture distributions, as well as to be used when truncated. See Dewitte (2020) <https://hdl.handle.net/1854/LU-8644700> for a description and application of methods available in this package.

Provides new types of omnibus tests which are generally much more powerful than traditional tests (including the Kolmogorov-Smirnov, Cramer-von Mises and Anderson-Darling tests),see Zhang (2002) <doi:10.1111/1467-9868.00337>.

Utilities are provided which are of use in the
    packages I have developed for dealing with
    distributions. Currently these packages are GeneralizedHyperbolic,
    VarianceGamma, and SkewHyperbolic and NormalLaplace. Each of these
    packages requires DistributionUtils. Functionality includes sample
    skewness and kurtosis, log-histogram, tail plots, moments by
    integration, changing the point about which a moment is
    calculated, functions for testing distributions using inversion
    tests and the Massart inequality. Also includes an implementation
    of the incomplete Bessel K function.

Implements S4 classes for probability models based on packages 'distr' and
            'distrEx'.