Numerical integration of continuously differentiable
    functions f(x,y) over simple closed polygonal domains.
    The following cubature methods are implemented:
    product Gauss cubature (Sommariva and Vianello, 2007,
    <doi:10.1007/s10543-007-0131-2>),
    the simple two-dimensional midpoint rule
    (wrapping 'spatstat.geom' functions), and
    adaptive cubature for radially symmetric functions via line
    integrate() along the polygon boundary (Meyer and Held, 2014,
    <doi:10.1214/14-AOAS743>, Supplement B).
    For simple integration along the axes, the 'cubature' package
    is more appropriate.

Provide easy methods to translate pieces of text.
  Functions send requests to translation services online.

Infer the genetic composition of individuals
    in terms of haplotype dosages for a haploblock, based
    on bi-allelic marker dosages, for any ploidy level.
    Reference: Voorrips and Tumino: PolyHaplotyper: haplotyping in polyploids based on bi-allelic marker dosage data.
    Submitted to BMC Bioinformatics (2021).

Kernel density estimation on the polysphere, (hyper)sphere, and
    circle. Includes functions for density estimation, regression estimation,
    ridge estimation, bandwidth selection, kernels, samplers, and homogeneity
    tests. Companion package to García-Portugués and Meilán-Vila (2025)
    <doi:10.1080/01621459.2025.2521898> and García-Portugués and Meilán-Vila
    (2023) <doi:10.1007/978-3-031-32729-2_4>.

A wrapper around the C++ library 'polylabel' from 'Mapbox',
    providing an efficient routine for finding the approximate pole of
    inaccessibility of a polygon, which usually serves as an excellent candidate
    for labeling of a polygon.

Creation of linkage maps in polyploid species from marker dosage
    scores of an F1 cross from two heterozygous parents. Currently works for outcrossing diploid, autotriploid, autotetraploid and autohexaploid species, 
    as well as segmental allotetraploids. Methods are described in a manuscript of Bourke et al. (2018) <doi:10.1093/bioinformatics/bty371>. Since version 1.1.0,
    both discrete and probabilistic genotypes are acceptable input; for more details on the latter see Liao et al. (2021) <doi:10.1007/s00122-021-03834-x>.