Functions for performing (external) multidimensional unfolding.
             Restrictions (fixed coordinates or model restrictions) are available for both row and column coordinates in all combinations.

Provides functions to help in fitting models to data, to
  perform Monte Carlo, sensitivity and identifiability analysis. It is
  intended to work with models be written as a set of differential
  equations that are solved either by an integration routine from
  package 'deSolve', or a steady-state solver from package
  'rootSolve'. However, the methods can also be used with other types of
  functions.

Create local, regional, and global explanations for any machine learning model with forward marginal effects. You provide a model and data, and 'fmeffects' computes feature effects. The package is based on the theory in: C. A. Scholbeck, G. Casalicchio, C. Molnar, B. Bischl, and C. Heumann (2022) <doi:10.48550/arXiv.2201.08837>.

Heterogeneity pursuit methodologies for regularized finite mixture regression by effects-model formulation proposed by Li et al. (2021) <arXiv:2003.04787>.

Generate planar and spherical triangle meshes,
    compute finite element calculations for 1- and 2-dimensional flat and curved
    manifolds with associated basis function spaces, methods for lines and
    polygons, and transparent handling of coordinate reference systems and
    coordinate transformation, including 'sf' and 'sp' geometries. The core
    'fmesher' library code was originally part of the 'INLA' package, and
    implements parts of "Triangulations and Applications" by
    Hjelle and Daehlen (2006) <doi:10.1007/3-540-33261-8>.

A fast class noise detector which provides noise score for each observations. The package takes advantage of 'RcppArmadillo' to speed up the calculation of distances between observations.

Provides a collection of functions to fit and explore single, multi-component and restricted Frequency Modulated Moebius (FMM) models. 'FMM' is a nonlinear parametric regression model capable of fitting non-sinusoidal shapes in rhythmic patterns. Details about the mathematical formulation of 'FMM' models can be found in Rueda et al. (2019) <doi:10.1038/s41598-019-54569-1>.