Implements both real-valued branches of the Lambert-W function
    (Corless et al, 1996) <doi:10.1007/BF02124750> without the need for
    installing the entire GSL.

Implementation of the methods described in Holzmann, Klar (2024) <doi: 10.1111/sjos.12733>.
    Lancaster correlation is a correlation coefficient which equals the 
    absolute value of the Pearson correlation for the bivariate normal distribution,
    and is equal to or slightly less than the maximum correlation coefficient 
    for a variety of bivariate distributions. Rank and moment-based estimators and 
    corresponding confidence intervals are implemented, as well as independence 
    tests based on these statistics.

Changes of landscape diversity and structure can be detected
    soon if relying on landscape class combinations and analysing patterns
    at multiple scales. 'LandComp' provides such an opportunity, based on
    Juhász-Nagy's functions (Juhász-Nagy P, Podani J 1983
    <doi:10.1007/BF00129432>). Functions can handle multilayered data.
    Requirements of the input: binary data contained by a regular square
    or hexagonal grid, and the grid should have projected coordinates.

Provides functions to estimate survival and a treatment effect using a landmark estimation approach.

Provides a function for classifying a landscape into different categories based on the Topographic Position Index (TPI) and slope. It offers two types of classifications: Slope Position Classification, and Landform Classification. The function internally calculates the TPI for the given landscape and then uses it along with the slope to perform the classification. Optionally, descriptive statistics for every class are calculated and plotted. The classifications are useful for identifying the position of a location on a slope and for identifying broader landform types.

Shared, dependency-light primitives for landscape-genetic network
  methods: a lightweight deme/landscape graph (vertex coordinates and an undirected
  edge list) with constructors from coordinates; genetic covariance and distance
  from biallelic or multiallelic data (the Yang-style normalized-dosage covariance
  and the Dyer-style multivariate covariance); and antisymmetric per-edge
  directional covariate builders (the gradient of a scalar potential, and the
  projection of a vector flow field). Used by 'terradish' (symmetric resistance)
  and 'dragonflow' (asymmetric gene flow). No compiled code.