Sampling from the Cholesky factorization of a Wishart random 
    variable, sampling from the inverse Wishart distribution, sampling from 
    the Cholesky factorization of an inverse Wishart random variable, sampling
    from the pseudo Wishart distribution, sampling from the generalized
    inverse Wishart distribution, computing densities for the Wishart 
    and inverse Wishart distributions, and computing the multivariate gamma 
    and digamma functions. Provides a header file so the C functions can be
    called directly from other programs.

One way to choose the number of principal components is via the reconstruction error. This package is designed mainly for this purpose. Graphical representation is also supported, plus some other principal component analysis related functions. References include: Jolliffe I.T. (2002). Principal Component Analysis. <doi:10.1007/b98835> and Mardia K.V., Kent J.T. and Bibby J.M. (1979). Multivariate Analysis. ISBN: 978-0124712522. London: Academic Press.

Calculates permutation tests that can be powerful for comparing two groups with some positive but many zero responses (see Follmann, Fay, and Proschan <DOI:10.1111/j.1541-0420.2008.01131.x>).

Resampling is a standard step in particle filtering and in
    sequential Monte Carlo. This package implements the chopthin resampler, which
    keeps a bound on the ratio between the largest and the smallest weights after
    resampling.

Learning the structure of graphical models from datasets with thousands of variables.
    More information about the research papers detailing the theory behind Chordalysis is available at
    <http://www.francois-petitjean.com/Research> (KDD 2016, SDM 2015, ICDM 2014, ICDM 2013).
    The R package development site is <https://github.com/HerrmannM/Monash-ChoR>.

Maximum likelihood estimation in respondent driven samples.

Choropleths are thematic maps where geographic regions, such as
    states, are colored according to some metric, such as the number of people
    who live in that state. This package simplifies this process by 1.
    Providing ready-made functions for creating choropleths of common maps. 2.
    Providing data and API connections to interesting data sources for making
    choropleths. 3. Providing a framework for creating choropleths from
    arbitrary shapefiles. 4. Overlaying those maps over reference maps from
    Google Maps.