Implements nonparametric density estimation with Averaged Shifted
    Histogram (ASH), Linear Blend Frequency Polygon (LBFP), and General Linear
    Blend Frequency Polygon (GLBFP) estimators. The package provides pointwise
    and grid-based estimation workflows, sparse-prefix grid-count computation,
    plotting helpers, and plug-in bandwidth selection. Methodological
    background follows Scott (1992) <doi:10.1002/9780470316849>, Terrell and
    Scott (1985) <doi:10.1080/01621459.1985.10477163>, and Carbon and
    Duchesne (2024) <doi:10.1007/s10463-023-00883-5>.

Fits multiple-group latent class analysis (LCA) for exploring 
    differences between populations in the data with a multilevel structure. 
    There are two approaches to reflect group differences in glca: 
    fixed-effect LCA (Bandeen-Roche et al (1997) <doi:10.1080/01621459.1997.10473658>;
    Clogg and Goodman (1985) <doi:10.2307/270847>) and nonparametric random-effect LCA 
    (Vermunt (2003) <doi:10.1111/j.0081-1750.2003.t01-1-00131.x>).

Enables calculation of image textures (Haralick 1973) 
    <doi:10.1109/TSMC.1973.4309314> from grey-level co-occurrence matrices 
    (GLCMs). Supports processing images that cannot fit in memory.

Calculates grey level co-occurrence matrix (GLCM) based texture measures (Hall-Beyer (2017) <https://prism.ucalgary.ca/bitstream/handle/1880/51900/texture%20tutorial%20v%203_0%20180206.pdf>; Haralick et al. (1973) <doi:10.1109/TSMC.1973.4309314>) of raster layers using a sliding rectangular window. It also includes functions to quantize a raster into grey levels as well as tabulate a glcm and calculate glcm texture metrics for a matrix.

The generalised lambda distribution, or Tukey lambda distribution, 
  provides a wide variety of shapes with one functional form.   
  This package provides random numbers, quantiles, probabilities, 
  densities and density quantiles for four different types of the distribution,
  the FKML (Freimer et al 1988), RS (Ramberg and Schmeiser 1974), GPD (van Staden
  and Loots 2009) and FM5 - see documentation for details.
  It provides the density function, distribution function, and Quantile-Quantile 
  plots.  
  It implements a variety of estimation methods for the distribution, 
  including diagnostic plots. 
  Estimation methods include the starship (all 4 types), 
  method of L-Moments for the GPD and FKML types, and a 
  number of methods for only the FKML type.  
  These include maximum likelihood, maximum product of spacings, 
  Titterington's method, Moments, Trimmed L-Moments and 
  Distributional Least Absolutes.