Algorithms to compute spherical k-means partitions.
  Features several methods, including a genetic and a fixed-point
  algorithm and an interface to the CLUTO vcluster program.

It's a Super K-Nearest Neighbor(SKNN) classification method with using kernel density to describe weight of the distance between a training observation and the testing sample. Comparison of performance between SKNN and KNN shows that SKNN is significantly superior to KNN.

Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of blocked and split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible. For details, see Morgan-Wall et al. (2021) <doi:10.18637/jss.v099.i01>.

The public available Danish SKS (Sundhedsvæsenets Klassifikationssystem) and 
    SNOMED (Systematized Nomenclature of Medicine) codes with labels. The labels are useful
    to sort and make sense of microdata in closed computing environments.
    Current as of april 2026 (SNOMED) and june 2026 (SKS).
    SNOMED <https://www.patobank.dk/snomed/> and 
    SKS <https://filer.sundhedsdata.dk/sks/data/skscomplete/>.

A tool to calculate sky illuminance values (in lux) for both sun and moon. The
 model is a translation of the Fortran code by Janiczek and DeYoung (1987)
 <https://archive.org/details/DTIC_ADA182110>.

Generates physically based sky environment maps and radiance
    samples using the spectral Hosek-Wilkie and Prague atmosphere models.
    Functions write high-dynamic-range 'OpenEXR' domes in latitude-longitude
    projections, compute per-direction RGB or 55-channel values, and optionally
    composite time-accurate star fields and moon phases. Features include
    automatic sun and moon positioning from date, time and location, support for
    sea-level and high-altitude observers, wide-spectrum coefficients, and
    multithreaded C++ acceleration for fast, high-resolution output. For model
    details, see Hosek and Wilkie (2012)
    <doi:10.1145/2185520.2185591>, Hosek and Wilkie (2013)
    <doi:10.1109/MCG.2013.18>, Wilkie et al. (2021)
    <doi:10.1145/3450626.3459758>, and Vevoda et al. (2022)
    <doi:10.1111/cgf.14677>.