Provides functions to perform the fitting of an adaptive mixture
    of Student-t distributions to a target density through its kernel function as described in
    Ardia et al. (2009) <doi:10.18637/jss.v029.i03>. The
    mixture approximation can then be used as the importance density in importance
    sampling or as the candidate density in the Metropolis-Hastings algorithm to
    obtain quantities of interest for the target density itself.

Implements techniques to estimate the unknown quantities
    related to two-component admixture models, where the two components
    can belong to any distribution (note that in the case of multinomial
    mixtures, the two components must belong to the same family).
    Estimation methods depend on the assumptions made on the unknown
    component density; see Bordes and Vandekerkhove (2010)
    <doi:10.3103/S1066530710010023>, Patra and Sen (2016)
    <doi:10.1111/rssb.12148>, and Milhaud, Pommeret, Salhi, Vandekerkhove
    (2024) <doi:10.3150/23-BEJ1593>. In practice, one can estimate both
    the mixture weight and the unknown component density in a wide variety
    of frameworks. On top of that, hypothesis tests can be performed in
    one and two-sample contexts to test the unknown component density (see
    Milhaud, Pommeret, Salhi and Vandekerkhove (2022)
    <doi:10.1016/j.jspi.2021.05.010>, and Milhaud, Pommeret, Salhi,
    Vandekerkhove (2024) <doi:10.3150/23-BEJ1593>). Finally, clustering of
    unknown mixture components is also feasible in a K-sample setting (see
    Milhaud, Pommeret, Salhi, Vandekerkhove (2024) 
    <https://jmlr.org/papers/v25/23-0914.html>).

Provides functions to perform global (genome-wide) and local admixture inference 
  from bi- and multi-allelic marker dosages (discrete or continuous) in polyploid species.

An interface for performing all stages of 'ADMIXTOOLS' analyses
    (<https://github.com/dreichlab/admixtools>) entirely from R. Wrapper functions
    (D, f4, f3, etc.) completely automate the generation of intermediate
    configuration files, run 'ADMIXTOOLS' programs on the command-line, and
    parse output files to extract values of interest. This allows users to focus
    on the analysis itself instead of worrying about low-level technical details.
    A set of complementary functions for processing and filtering of data in
    the 'EIGENSTRAT' format is also provided.